issn 1451 - 9372(print) issn 2217 - 7434(online) … no4_p465-568_oct-dec...issn 2217 - 7434(online)...

ISSN 1451 - 9372(Print)ISSN 2217 - 7434(Online)OCTOBER-DECEMBER 2015Vol.21, Number 4, 465-568

www.ache.org.rs/ciceq

Journal of the Association of Chemical Engineers of Serbia, Belgrade, Serbia

EDITOR-In-Chief

Vlada B. Veljković Faculty of Technology, University of Niš, Leskovac, Serbia

E-mail: [email protected]

ASSOCIATE EDITORS Jonjaua Ranogajec

Faculty of Technology, University of Novi Sad, Novi Sad, Serbia

Srđan PejanovićDepartment of Chemical Engineering, Faculty of Technology and Metallurgy,

University of Belgrade, Belgrade, Serbia

Milan Jakšić ICEHT/FORTH, University of Patras,

Patras, Greece

EDITORIAL BOARD (Serbia) Đorđe Janaćković, Sanja Podunavac-Kuzmanović, Viktor Nedović, Sandra Konstantinović, Ivanka Popović

Siniša Dodić, Zoran Todorović, Olivera Stamenković, Marija Tasić, Jelena Avramović

ADVISORY BOARD (International)

Dragomir Bukur

Texas A&M University, College Station, TX, USA

Milorad Dudukovic

Washington University, St. Luis, MO, USA

Jiri Hanika

Institute of Chemical Process Fundamentals, Academy of Sciences of the Czech Republic, Prague, Czech Republic

Maria Jose Cocero

University of Valladolid, Valladolid, Spain

Tajalli Keshavarz

University of Westminster, London, UK

Zeljko Knez

University of Maribor, Maribor, Slovenia

Igor Lacik

Polymer Intitute of the Slovak Academy of Sciences, Bratislava, Slovakia

Denis Poncelet

ENITIAA, Nantes, France

Ljubisa Radovic

Pen State University, PA, USA

Peter Raspor

University of Ljubljana, Ljubljana, Slovenia

Constantinos Vayenas

University of Patras, Patras, Greece

Xenophon Verykios

University of Patras, Patras, Greece

Ronnie Willaert

Vrije Universiteit, Brussel, Belgium

Gordana Vunjak Novakovic

Columbia University, New York, USA

Dimitrios P. Tassios

National Technical University of Athens, Athens, Greece

Hui Liu

China University of Geosciences, Wuhan, China

FORMER EDITOR (2005-2007) Professor Dejan Skala

University of Belgrade, Faculty of Technology and Metallurgy, Belgrade, Serbia


Vol. 21 Belgrade, October-December 2015 No. 4

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CONTENTS

Jun Tan, Xiaoyan Wei, Yuxia Ouyang, Rui Liu, Ping Sun, Juhong Fan, Evaluation of insoluble xanthate and crosslinked starch-graft-polyacrylamide-co-sodium xanthate for the adsorption of Cu(II) in aqueous solutions ............................................................................. 465

Ogbemudia Joseph Ogbebor, Felix Ebhodaghe Okieimen, David Ehioghilen Ogbeifun, Uzoma Ndubuisi Okwu, Organomodified kaolin as filler for natural rubber .............. 477

Vesna M. Pavelkić, Tanja P. Brdarić, Marija P. Petrović, Gavrilo M. Šekularac, Milica G. Košević, Lato L. Pezo, Marija A. Ilić, Application of Peleg model on mass transfer kinetics during osmotic dehydratation of pear cubes in sucrose solution ................................................... 485

Rongyan Shen, Fang Liu, Te Li, Xia Xu, Yuting Liang, Xingqing Zhao, Wenyi Zhang, Treatment of 2-diazo- -4,6-dinitrophenol wastewater using TiO2/SiO2 composite film in a photocatalytic reactor .......................... 493

Milutin M. Milosavljević, Ivan M. Vukićević, Veis Šerifi, Jas-mina S. Markovski, Ivana Stojiljković, Dušan Ž. Mijin, Aleksandar D. Marinković, Optimization of the syn-thesis of N-alkyl and N,N-dialkyl thioureas from waste water containing ammonium thiocyanate ........................... 501

Sheng Fang, Li-Ping Wang, Ting Wu, Mathematical modeling and effect of blanching pretreatment on the drying kinetics of Chinese Yam (Dioscorea opposita) .................. 511

Zorana Arsenijević, Tatjana Kaluđerović Radoičić, Mihal Đuriš, Željko Grbavčić, Experimental investigation of heat transfer in three-phase fluidized bed cooling column ................................................................................ 519

Vesna S. Cvetković, Luka J. Bjelica, Nataša M. Vukićević, Jovan N. Jovićević, Alloy formation by Mg under-potential deposition on Al from nitrate melts ...................... 527

Rajamohan Natarajan, Jamila Al-Sinani, Saravanan Viswa-nathan, Performance evaluation and kinetic studies on removal of benzene in up-flow tree bark based biofilter ....... 537

D. Tiroutchelvame, V. Sivakumar, J. Prakash Maran, Mass transfer kinetics during osmotic dehydration of Amla (Emblica officinalis L.) cubes in sugar solution .................. 547

Contents: Vol. 21, Issues 1–4, 2015 .............................................. 561

Author Index, Vol. 21, 2015 .......................................................... 565

Activities of the Association of Chemical Engineers of Serbia in 2015 are supported by: - Ministry of Education, Science and Technological Development, Republic of Serbia - Hemofarm Koncern AD, Vršac, Serbia - Faculty of Technology and Metallurgy, University of Belgrade, Belgrade, Serbia - Faculty of Technology, University of Novi Sad, Novi Sad, Serbia - Faculty of Technology, University of Niš, Leskovac, Serbia - Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Serbia

Chemical Industry & Chemical Engineering Quarterly

Available on line at Association of the Chemical Engineers of Serbia AChE www.ache.org.rs/CICEQ

Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015) CI&CEQ

465

JUN TAN1,2

XIAOYAN WEI1 YUXIA OUYANG1

RUI LIU2 PING SUN1,2

JUHONG FAN3 1Department of Chemical and Textile Engineering of Nanhu

College, Jiaxing University, Jiaxing, Zhejiang Province, China

2College of Biological and Chemical Engineering, Jiaxing

University, Jiaxing, Zhejiang Province, China

3Zhejiang Provincial Key Laboratory of Water Science and

Technology, Department of Environment, Yangtze Delta Region Institute of Zhejiang,

Jiaxing, Zhejiang Province, China

SCIENTIFIC PAPER

UDC 547.815:678.745.8:544.723:66

DOI 10.2298/CICEQ141102002T

EVALUATION OF INSOLUBLE XANTHATE AND CROSSLINKED STARCH-GRAFT- -POLYACRYLAMIDE-CO-SODIUM XANTHATE FOR THE ADSORPTION OF Cu(II) IN AQUEOUS SOLUTIONS

Article Highlights • The adsorption capacity of CSAX for Cu(II) was higher than that of ISX • The removal efficiency of ISX for Cu(II) was better than that of CSAX • For CSAX, more N or S do not mean higher removal efficiency or higher adsorption

capacity • The adsorption mechanism of CSAX for Cu(II) is the physical adsorption and ion

exchange • CSAX was an alternative to ISX when treating heavy metal wastewater with turbidity Abstract

The effectiveness of insoluble xanthate (ISX) and crosslinked starch-graft- polyacrylamide-co-sodium xanthate (CSAX) for Cu(II) removal from waste-water was evaluated. The two types of xanthates were characterized by SEM, XRD, FTIR and elemental analysis. Also, the factors influencing adsorption behaviors of copper ions from aqueous solutions were investigated. The results indicated CSAX had higher absorption capacity for Cu(II) than ISX because it contained more N and S. While as far as the removal efficiency was concerned, ISX was better than CSAX for its strong ligand–CSS– groups. The removal efficiency of Cu(II) onto CSAX and ISX increased with the increase in pH. The mechanism for Cu(II) adsorption was ionic exchange for ISX whereas both ion exchange and physical adsorption contributed to adsorption by CSAX. The adsorption kinetics of ISX and CSAX for Cu(II) were favorably described by the pseudo-second-order kinetic model, and the adsorption isotherms were described well with the Freundlich isotherm model. The study with synthetic wastewater showed CSAX was a worthwhile alternative to the traditional ISX only when the wastewater contained both Cu(II) and turbidity.

Keywords: insoluble starch xanthate, crosslinked starch-graft-polyacryl-amide-co-sodium xanthate, Cu(II) removal, adsorption kinetics, adsorp-tion isotherm.

Water pollution caused by heavy metals has been a worldwide concern due to their hazardous and toxic effects on the environment, human beings, and animals. In the past few years, the removal of heavy metal ions from sewage and industrial wastewater has been given lots of attention, particularly in China

Correspondence: X. Wei, Department of Chemical and Textile Engineering of Nanhu College, Jiaxing University, Jiaxing 314001, Zhejiang Province, China. E-mail: [email protected] Paper received: 2 November, 2014 Paper revised: 9 January, 2015 Paper accepted: 20 January, 2015

where soil and water have been seriously polluted by heavy metals [1-3]. Conventional methods for the removal of heavy-metal ions from wastewater inc-luding reduction precipitation, ion exchange and ads-orption, electrochemical reduction, evaporation, rev-erse osmosis, and direct precipitation [4,5]. Among these methods, adsorption is generally preferred because of its high efficiency, easy management, rel-atively low cost, and especially availability of different adsorbents [6]. Therefore, the search for new highly effective, environmental-friendly and economic-viable adsorbents has become the focus of many studies [7].

J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE… Chem. Ind. Chem. Eng. Q. 21 (4) 465−476 (2015)

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In this respect, many natural polysaccharides and their derivatives containing various functional groups (chitin and its derivatives, modified cellulose, and modified starch, etc.) have gained great interest [8-11]. Starch is the most abundant biopolymer after cellulose and chitosan. In contrast to cellulose, starch is water-soluble, making it easy to be modified to incorporate active functional groups to improve its applications [12-15]. In 1970s, Wing et al. reported that insoluble starch xanthate (ISX) prepared by xan-thation of a highly crosslinked starch, was effective for removing various heavy metal ions in the aqueous medium [16-19]. The manufacture process of this derivative as xanthation is a relatively simple, and starch itself is a cheap biopolymer; thus it is manu-factured and widely applied. Recently, Chang et al. have synthesized a novel crosslinked starch-graft-polyacrylamide-co-sodium xanthate (CSAX) by cross- -linking, grafting copolymerization and xanthation reaction, and stated that the CSAX is more effective than ISX in removing heavy metal ions [20-22].

A comparative study of ISX vs CSAX for the removal of heavy metals would greatly facilitate the choice of the more efficient adsorbent (ISX or CSAX). Cu(II) is a common and highly toxic heavy metal pol-lutant because it is widely used in paints and pig-ments, paper and pulp, fertilizer manufacturing, wood preservatives, and metal cleaning. Excessive intake of Cu(II) can be accumulated in the livers of human and animals, which leads to damage of liver and kid-ney, anemia, immunotoxicity, etc. [23]. The U.S. Envi-ronmental Protection Agency (U.S. EPA) requires that copper in drinking water does not exceed 1.3 mg/L. Therefore, in the present work, efforts were made to study the adsorption characteristics of Cu(II) in aque-ous solutions onto ISX and CSAX. The two adsor-bents were characterized by SEM, XRD, FTIR and elemental analysis. The influence of the element con-tent, adsorbent dosage, solution pH, and contact time on the absorption performance was investigated. In addition, their absorption mechanism, isotherm and kinetics were also studied, which have not been reported in the previous literature.

EXPERIMENTAL

Materials

The cornstarch used was food grade (Tianjin DingFeng Factory, China). Epichloro-hydrin (EPI), acrylamide (AM), and ceric ammonium nitrate (CAN) (AR, Shanghai Chemical Reagent Factory, China) were used as the cross-linking reagent, graft mono-mer and initiator, respectively. Analytical grade ace-

tone, potassium hydroxide, hydrochloric acid and ethanol were supplied by Hangzhou Chemical Reagent Factory, China. The stock solution of 300 mg/L Cu(II) was prepared using CuSO4·5H2O (AR, Shanghai Chemical Reagent Factory, China) and then diluted to appropriate concentrations for each test. Distilled water was used in the polymerization and preparation of the buffer solutions.

Preparation of ISX and CSAX

The synthesis procedure and the chemicals used for the preparation of ISX are described in Wing’s study [17].

Step 1: Preparation of crosslinked starch. 50 g of corn starch was added into 75 mL 1% NaCl sol-ution in a beaker and heated to 30 °C in a water bath. 20 mL 15 mass% KOH solution was added to this slurry, then 3.5 mL epichlorohydrin was added in dropwise. The reaction was kept for 16 h to obtain the crosslinked starch. The product was washed with deionized water and ethanol, then filtered by vacuum and dried at 133 °C for 2 h.

Step 2: Xanthation of crosslinked starch. Pre-pared slurry with 5 g crosslinked starch and 20 mL distilled water, then heated at 30 °C in a water bath. A mixture of 4 mL H2O containing 1 g NaOH and a cer-tain amount of CS2 were added in the above liquid and stirred for 2 h. The precipitate was washed with distilled water, ethanol, acetone, and dry in vacuum oven at 27 °C to a constant weight.

Three different ISXs were prepared and design-ated as ISX1, ISX2, and ISX3. The sulfur content in the three different ISXs was controlled by the addition of CS2 at 0.3 g, 0.7 g, and 1.25 g with 5.0 g cross-linked starch in the xanthation step, respectively.

The synthesis of CSAX was conducted in accordance with the procedure described in Chang’s study [20].

Step 1 was to prepare cross-linked starch, which was the same as step 1 of ISX.

Step 2 was the preparation of cross-linked starch-grafted polyacrylamide (CSA).

3.0 g of crosslinked starch was mixed with 50 mL of distilled water to prepare starch slurry at 80 °C in a water bath. Then, 6.0 g of AM monomer and 10 mL CAN (which was used as radicals intiator) solution (6 mmol L−1) were added to the slurry. The expe-riments were conducted under a nitrogen atmosphere with constant stirring at 35 °C for 3 h (the grafting efficiency reached the maximum value of 72.7% and the molecular weight of graft PAM pendant chain reached 2.67×107). Then the graft copolymer was washed with acetone to remove the unreacted mono-


467

mer. Afterward, it was filtered and dried at 50 °C in a vacuum oven.

Step 3 was the preparation of CSAX. CSA (1 g) was xanthated by dropwise addition

of 3 mol/L NaOH and a certain amount of CS2 into the sealed conical flask and stirring magnetically at 30 °C in a water bath for 3 h until it turned saffron yellow. The precipitate was washed with acetone (50%) three times, pure acetone one time, filtered and dried at 27 °C to a constant weigh.

As for CSAXs, three different amounts of CS2 (0.8, 1.7 and 3.5 g) were added with 1.0 g crosslinked starch-graft-polyacrylamide in the process of xan-thation to prepare CSAX1, CSAX2 and CSAX3.

Characterization methods

X-ray diffraction (XRD) patterns of ISX and CSAX were obtained using a DX-2600 X-ray diffractometer (Dandong Fangyuan Instrument Company, China) operating at 40 kV and 40 mA. The surface mor-phology of ISX and CSAX was examined using a S-4800 scanning electron microscope (Hitachi, Japan). The FT-IR spectra of ISX and CSAX were recorded on the NEXUS470 (Nicole Instrument Corporation, USA) using the KBr dispersion method. Elemental analysis of dry samples was performed on a Flash EA-1112 elemental analyzer (Thermo Fingnigan Cor-poration, Italy), and carbon, hydrogen, nitrogen and sulfur contents were determined.

Adsorption experiments

In general, batch adsorption experiments were conducted in 250 mL conical flasks containing 100 mL of Cu(II) solution with the initial concentration of 30 mg/L (unless otherwise stated) and a certain amount of adsorbent. The mixtures were shaken at 180 rpm in a thermostatic water-bath shaker with con-trolled adsorption time and temperature. After adsorp-tion equilibrium was reached, the solution was filtered and residual Cu(II) and Na+ concentrations in the fil-trate was analyzed by an AA800 atomic absorption spectrometer (PerkinElmer, USA).

The effect of solution pH on the Cu(II) adsorp-tion was studied in the pH range from 2 to 7 at 298 K. The pH was adjusted using 0.1 M NaOH or 0.1 M HCl solutions. The adsorption isotherm was studied at dif-ferent initial copper concentrations ranging 30-300 mg/L at 298 K at an initial pH value of 5.3. All our experimental data were the average of triplicate determinations. The relative standard errors of the data were less than 5%.

The amount of Cu(II) adsorbed on the adsorbent (Q in mg/g) was calculated using Eq. (1):

−= 0( )tc c VQW

(1)

where C0 and Ct (mg/L) are the initial and final con-centrations of Cu(II) at time t, respectively; V is the total volume of the aqueous solution (L); W is the mass of adsorbent (g). The removal efficiency of Cu(II) was calculated using Eq. (2):

Removal efficiency (%) = −0 e

0

100c c

c (2)

RESULTS AND DISCUSSION

Characterizations of the two adsorbents

Scanning electron microscopy (SEM) was used to study the granular morphology of starch, ISX and CSAX.

Figure 1 shows that native starch granules appeared dispersedly with a smooth, oval, regular surface, and had particle diameter with about 10 μm. While the granules of ISX possessed obvious defor-mations because the cross linking and xanthation reactions led to an altered uneven surface, creating pores and adhension of small particles on the sur-face, but the particle diameter did not change obvi-ously. CSAX showed a rougher surface, and the par-ticles were conglomerated closely. Inaddition, the gra-nules became significantly bigger than starch or ISX due to graft copolymerization, and particle diameter increased to over 100 μm.

The XRD patterns of starch, ISX and CSAX are shown in Figure 2. The original starch shows scat-tering at 2θ 15.18, 17.15 and 23.19°, representing the diffraction peaks of the hydroxyl group, which are characteristic peaks of starch, However, the XRD curves of ISX express traditional “A” style, and only have a wide amorphous diffraction peak at 20.38°, which means that the crystallinity of ISX3 decreased remarkably than natural starch [24]. The diffraction spectrum of CSAX becomes much weaker than ISX, which indicates that its crystallinity was further red-uced. It is attributed to the fact that the aggregation phase of original starch was changed from a semi-crystalline state to an amorphous aggregation state during the cross-linking and graft polymerization.

The chemical structures of starch, ISX and CSAX were indentified with FTIR spectroscopy (Fig-ure not shown). For CSAX, a broad absorption band at 3418 cm−1 is due to the –NH stretching of the –NH2 group (overlapped by –OH of starch). A smaller peak at 2931 cm−1 is assigned to the –CH stretching vib-rations. Absorption peaks at 1658 and 1563 cm−1 are –C=O and –C=O (hydrogen bonded) stretching vib-

J. TAN et al.: EVALUATION OF INSOLUBLE XANTHATE… CI&CEQ 21 (4) 465−476 (2015)

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Figure 1. SEM images of starch (a,b), ISX (c,d) and CSAX (e,f).

10 20 30 40 50 60Two-Theta(deg)

starch

ISX

CSAX

Rela

tive

Inte

nsity

(%)

Figure 2. XRD patterns of starch, ISX, and CSAX.

ration of the –CONH2 groups, and the peaks at 1750 cm−1 is for –COO– stretching. The absorption peak at 2450 cm−1 corresponds to the –SH stretching vibration of the xanthate unit. The –CSSH groups’ spectra are displayed in the ranges of 1240–1200 cm−1, 1140–

–1110 cm−1, and 1070–1029 cm−1. The peak at 883 cm−1 may be attributed to the deformation of –CSS–

[20]. Therefore, it is suggested that CSAX was syn-thesized successfully. For ISX, there were strong characteristic peaks at 1512 cm-1 for –C=S and 853


469

cm-1 for the –CSS– deformation [17], indicating xan-thate groups were induced on the starch molecular chain.

Elemental analysis of the dry samples shows the different element content of ISXs and CSAXs, and the results are shown in Table 1.

Table 1. Elemental analysis of CSAXs (mass%)

Sample C H N S

ISX1 25.70 4.72 0.00 0.71

ISX2 26.04 4.35 0.00 1.98

ISX3 26.87 4.11 0.00 2.46

CSAX1 29.81 5.07 3.09 8.32

CSAX2 30.29 5.26 3.65 5.03

CSAX3 32.62 5.58 4.17 3.95

Effect of adsorbent dosage and element contents on Cu(II) removal

The effects of the sulfur content and adsorbent dosage on the adsorption of Cu(II) on ISXs and CSAXs are shown in Figure 3. It shows that an inc-rease in the adsorbent dosage resulted in an increase in removal efficiency of Cu(II), then the removal effi-ciency leveled off in all cases. This was due to the availability of more binding sites initially when the adsorbent dosage increased, and then the adsorption equilibrium was reached after a certain dosage.

In Figure 3a, Cu(II) removal efficiency was inc-reased with the increase of sulfur contents in ISXs with the order of: ISX3 > ISX2 > ISX1. At 50 mg/L of adsorbent dosage removal of Cu(II) was found to be 92.29% for ISX3, 82.69% for ISX2 and 78.27% for

ISX1, respectively. With 200 mg/L dosage, the rem-oval efficiency for Cu(II) was 99.91, 99.15 and 98.68% for the three ISXs, respectively. It is evident that the difference in Cu(II) removal efficiency of the three ISXs was more significant at low adsorbent dosage, and the removal efficiency was almost the same at high adsorbent dosage. For ISXs, the optimum rem-oval efficiency of 99.89% was obtained at an dosage level of 150 mg/L. Therefore a dosage of ISX, ISX3 with 150 mg/L was used in the following adsorption experiments.

In Figure 3b, Cu(II) removal efficiency did not increase with the increase of the sulfur content in CSAX. However, it increased gradually with the inc-rease of S content from 3.95 to 5.03% and N content from 4.17 to 3.65%, and it declined with the further increase of S content from 5.03 to 8.32% and inc-rease of N content from 3.65 to 3.09%. The Cu(II) removal efficiency may relate to the ratio of N content to S content. When the N content was high (4.17%), it induced a high molecular weight of polymers and seg-mental overlapping of some grafted chains; when the S content was too low, there were not enough xan-thate groups. It was not favorable for the adsorption in both cases. However, the Cu(II) removal was not optimal when the N content was low (3.09%) and S content was high (8.32%). It seems that a balance would exist between the two elemental contents [25], and only CSAX2 (N: 3.65% and S: 5.03%) exhibited the maximum Cu(II) removal efficiency of 94.17% at the dosage of 50 mg/L. For CSAX1 and CSAX3, their maximum removal efficiency of Cu(II) was 83.1 and 88.07%, which was always lower than CSAX2 even at

0 100 200 300 40075

80

85

90

95

100

ISX3(S%=2.46) ISX2(S%=1.98) ISX1(S%=0.71)

Rem

oval

effi

cien

cy(%

)

The dosage of ISX(mg/L)0 100 200 300 400 500

75

80

85

90

95

100

CSAX2(S%=5.03) CSAX3(S%=8.32) CSAX1(S%=3.95)

Rem

oval

effi

cien

cy(%

)

The dosage of CSAX(mg/L)(a) (b)

Figure 3. Effect of ISXs’ (a) and CSAXs’ (b) sulfur content and dosage on the removal of Cu(II).


470

high dosages. Hence, the following experiments on CSAX adsorption were carried out at the adsorbent dosage of 50 mg/L using CSAX2 as the absorbent.

The removal efficiency and adsorption capacity are the two main characteristics for evaluating the adsorption ability of an adsorbent. The adsorption capacity is related to the quantity of effective func-tional groups, and the removal efficiency is depended on the binding affinity between effective functional groups and metal ions, so a high adsorption capacity does not mean high removal efficiency. For CSAX, there were many grafted pendant chain polyacryl-amides [26], the amide groups can bind Cu(II), and the removal efficiency of crosslinked starch-grafted polyacrylamide(CSA) for Cu(II) was 76%. In CSAX, there were not only amide groups but also xanthate groups, and the append –CSS– groups increased the removal efficiency to be above 90%. The adsorption capacity was 567.42 mg/g for CSAX2, which was much higher than that of 199.78 mg/g for ISX3 at their optimal adsorbent dosages. This was attributed to more functional groups in CSAX2，which included amide groups on the pendant chain and xanthate groups on the starch main chain. However, CSAX2 showed a lower removal efficiency for copper ion than ISX3 although CSAX2 (S: 5.03%) had a much higher surfur content than that of ISX3 (S: 2.46%). The reasons may be: first, the binding affinity of amide group for Cu(II) was weaker than the strong ligand -CSS- groups, because the bond atom in –CSS–

groups was S, the chelate complex formed between metal ions and S was very stable, and the solubility product (Ksp) values of metal sulfides are the lowest in all insoluble metal salts and metal hydroxides [27]; second, the steric hinderance effect of polyacrylamide pendant chains in CSAX inhibited the chelation of Cu(II) and –CSS– groups, and greatly reduced the utilization of –CSS– groups, which was much lower than that of ISX. That’s also the reason that the rem-oval efficiency for Cu(II) reached 99.91% at high dosages of ISX3 with only –CSS– groups.

Effects of pH on Cu(II) removal

The influence of the initial pH on the adsorption of Cu(II) onto ISX and CSAX was examined in the pH range of 2.0–7.0 (Figure 4). Copper is present in aqueous solution in the forms of Cu2+, Cu(OH)+ or Cu(OH)2. At pH ≤ 5, Cu(II) ions are the main species in the solution[28]. In Figure 4, it can be seen that the removal efficiency of Cu(II) of ISX or CSAX attained 45–55% even at pH 2; this was because the pKa value for the xanthate-xanthic acid dissociation was rep-orted to be 1.70 [29]. The xanthate groups existed in

the form of CSS– at pH 2, which could bind Cu(II) through electrostatic attraction. When pH increased, more xanthogenic acid groups of absorbents could ionize to negative xanthogenic acid radical groups, so that the chelation between xanthogenic acid radicals and Cu2+ increased, leading to high removal efficiency of Cu(II). When pH exceeded 4.0, the capacity of CSAX increased still while that of ISX kept constant.

2 3 4 5 6 740

50

60

70

80

90

100

Rem

oval

effi

cien

cy (%

)

pH

CSAX ISX

Figure 4. Effect of pH on the removal of Cu(II) by

CSAX and ISX.

The effect of pH can be explained by pHpzc values. The pHpzc of ISX and CSAX are 7.16 and 7.93, respectively. When pHs of solutions were lower than pHpzc of ISX or CSAX, the surface of the ads-orbents was positively charged and unfavorable for binding Cu2+. Generally, the net positive charge dec-reased with increasing pH value and leaded to dec-rease in the repulsion between the sorbent surface and metal ions, thus the adsorption capacity was enhanced. The removal efficiency of Cu(II) of ISX or CSAX attained 45–55% even at pH 2, indicating that initial pH has much smaller influence on ISX or CSAX because of the presence of strong acid xantate groups that are difficult to be protonated. These neg-ative groups have high affinity for the binding of posi-tive charged metal ions, even at a relatively low pH, probably by means of the ion exchange [30].

In order to study the probable mechanisms for Cu(II) interaction with ISX and CSAX, concentrations of Cu(II) and sodium were detected before and after the absorption. When copper concentration was rem-oved from 30 to 1.64 ppm (decreased by 0.443 mmol) with 50 mg/L CSAX at pH 5, the simultaneous release of sodium into the filtrate was increased from 0 to 5.89 ppm (increased by 0.256 mmol). The mole ratio (Cu:Na) corresponding to the changes was 1:0.58, and ionic exchanges between Cu and Na did not


471

occur in the theoretical ratio of 1:2. This can be exp-lained as follows: the amide groups on the PAM pen-dant chains of CSAX can bind Cu(II) as mentioned before, so chemical absorption also contributed to the reaction between Cu ions and CSAX. Moreover, some of the free metal ions possibly remained inside the granule due to the porous and layered structure of CSAX, interacting electrostatically with the starch chains. Therefore chemical interactions and the phys-ical entrapments of Cu(II) could be two additional mechanisms for Cu(II) removal by CSAX. For ISX, Cu(II) concentration was decreased from 30 to 0.58 ppm and meanwhile sodium concentration was inc-reased from 0 to 9.89 ppm in the filtrate with 150 mg/L ISX at pH 5; the mole ratio between Cu adsorbed and Na desorbed was 1:1.9, nearly to the theoretical ratio of 1:2, so the adsorption mechanism for Cu(II) xan-thate was mainly ionic exchange.

Adsorption kinetics

The removal efficiency of Cu(II) adsorbed on ISX and CSAX at different time are presented in Figure 5.

0 10 20 30 40 50 6065

70

75

80

85

90

95

100

t(min)

Rem

oval

effi

cien

cy (%

)

CSAX ISX

Figure 5. Effect of contract time of Cu(II) ions adsorption onto

ISX and CSAX.

The removal efficiency of Cu(II) on ISX and CSAX increased rapidly in the initial stage, and ISX reached equilibrium rapidly at 10 min while it was 60 min for CSAX. This indicates that Cu(II) can rapidly chelate with the xanthate groups of ISX, and the ads-orption time of CSAX was relatively long because of the steric effect of graft macromolecules. Pseudo- -first-order (Eq.(3)) and pseudo-second-order (Eq.(4)) kinetic models were applied to determine kinetic para-meters and explain the mechanism of Cu(II) on ISX and CSAX [31,32]:

= − −e 1[1 exp( )]tQ Q k t (3)

=+

22 e

2 e1tk Q tQ

k Q t (4)

where Qe and Qt (all in mg/g) are the adsorption amounts of Cu(II) on the adsorbent at equilibrium and at any time t, respectively; k1 is the rate constant of the pseudo-first-order adsorption; and k2 is the rate constant of the pseudo-second-order kinetics. The experimental data before adsorption equilibrium was used to assess the adsorption kinetics, and the cal-culated kinetic parameters are tabulated in Table 2.

It is clear that the correlation coefficient (R2) of the pseudo-second-order kinetic model (0.9999 and 0.9997 for ISX and CSAX) is much higher than that of the pseudo-first-order kinetic model (0.9768 and 0.9038 for ISX and CSAX). Besides, the adsorption capacities calculated (Qe (cal.)) with the pseudo-sec-ond-order model (200.249 and 556.237 mg/g for ISX and CSAX) are close to the experimental results (Qe (exp.)) (199.124 and 558.010 mg/g for ISX and CSAX). Therefore, the adsorption process of Cu(II) onto ISX and CSAX followed the pseudo-second- -order kinetic model for the whole adsorption process. The similar observations were reported on the ads-orption of Cu(II) from aqueous solution using ads-orbents with active groups，such as phosphate group [24], amino group [33], and hydroxyl group [34].

Table 2. Kinetic parameters for Cu(II) adsorption onto ISX and CSAX

Model Parameter ISX CSAX

Pseudo-first-order k1 / min–1 1.67134 0.65511

Qe / mg g–1 198.51239 527.29175

R2 0.72932 0.78051

Pseudo-second-order k2 / g mg–1 min–1 0.0599 0.002337

Qe / mg g–1 200.24925 556.23766

R2 0.99721 0.9869

Intraparticle ki / mg g–1 min–1/2 0.95922 20.42736

C 194.00207 423.7052

R2 0.5263 0.68039


472

The adsorption capacity of CSAX was higher than ISX, mainly due to its higher molecular mass and more active groups on its surface as discussed above. However, the values of k2 for ISX were much higher than those of CSAX, indicating that the ads-orption rate of ISX was faster than that of CSAX. A reasonable explanation of that is an easier access of the functional groups bound to Cu(II) for ISX than CSAX.

In general, the adsorption process may be des-cribed in three steps: mass transfer from fluid phase to the particle surface across the boundary layer, dif-fusion within the porous particle, and adsorption itself onto the surface. Considering the pseudo second-order model cannot identify the diffusion mechanism, the intraparticle diffusion model was then tested as: [35]:

= +12

itQ k t C (5)

where ki is the intraparticle diffusion rate constant (mg g−1 min−1/2) and C is the intercept. The intraparticle diffusion model was utilized to determine the rate-limiting step of the sorption process. If the regression of qt versus t1/2 is linear and passes through the origin (C = 0), then intraparticle diffusion is the sole rate-limiting step. In the present study, neither of plots passed through the origin and present multilinearity, indicating that three steps take place (figure of Qt versus t1/2 not shown), the first, sharper portion may be considered as an external surface adsorption or faster adsorption stage. The second portion describes the gradual adsorption stage, where intraparticle dif-fusion is rate-controlled. The third portion is attributed to the final equilibrium stage, where intra-particle dif-fusion starts to slow down due to the extremely low adsorbate concentrations in the solution [30]. The values of R2, obtained from the plots of intra-particle diffusion kinetics are lower than that of the pseudo-second-order model (Table 2) but this model indicates that the adsorption of Cu(II) onto ISX and CSAX may be followed by an intra-particle diffusion model up to 10 min. This indicates that although intraparticle dif-fusion was involved in the adsorption process, it was not the rate-controlling step.

Adsorption isotherm

In this study, Langmuir, Freundlich and D–R iso-therm models were applied to analyze the experi-mental data.

The Langmuir isotherm model, which is valid for monolayer adsorption onto a surface with finite num-ber of homogenous sites, is expressed as follows [36]:

= +e e

e m m

1C CQ Q b Q

(6)

The Freundlich isotherm model, which is valid for multilayer adsorption on a heterogeneous ads-orbent surface with sites that have different energies of adsorption, is expressed as follows [37]:

= +e f e1

lg lg lgQ K Cn

(7)

where Qm is the maximum adsorption amounts of Cu(II) in aqueous solutions at equilibrium (mg/g), b is the Langmuir constant (L/mg), and Kf (mg/g) and n are the Freundlich constants.

The parameters of the isotherm models deter-mined from experimental data are summarized in Table 3. The relatively high correlation coefficients (R2 in range 0.995-0.999) indicate that the experi-mental data fitted with the Freundlich isotherm model better than the Langmuir isotherm under the studied concentration range. The value of 1/n was less than 1, indicating favorable adsorption of Cu(II) onto ISX and CSAX. The Freundlich constant Kf of CSAX was higher than that of ISX, indicating that the adsorption capacity of CSAX for Cu(II) ions was higher.

Table 3. Langmuir, Freundlich and D–R parameters for Cu(II) adsorption onto ISX and CSAX

Model Parameter ISX CSAX

Langmuir Qm / mg g–1 466.877 2229.856

b / L mg–1 1.8243 0.0615

R2 0.9765 0.9599

Freundlich Kf 222.844 240.552

1/n 0.2633 0.5183

R2 0.9995 0.9978

D–R Qm / mg g–1 130.564 12268.832

KD / mol2 Kj–2 0.00204 0.00615

E / kJ mol–1 15.66 9.01

R2 0.9792 0.9802

The D–R isotherm model can be applied to distinguish between physical and chemical ads-orption. The linearized D–R isotherm model can be written as [38]:

ε= − D2

e mln lnQ Q K (8)

where KD is the constant related to adsorption energy (mol2/kJ2); ε is the Polanyi potential, which is equal to RTln(1+1/Ce); R is the universal gas constant (kJ/(mol K)); T is the temperature (K). The values of Qm and KD which were determined from the slope and intercept of the ln Qe versus ε2 plots (figure not shown) are


473

listed in Table 3. The relatively high correlation coefficients (R2 in range 0.979–0.980) reflect that the experimental data agreed well with the D–R isotherm model. The mean free energy of adsorption (Ea in kJ/mol), defined as the free energy change when 1 mol of ion is transferred to the surface of the solid from infinity in solution, can be calculated as follows:

−= 1/2a D(2 )E K (9)

It is known that the magnitude of Ea is useful for estimating the type of adsorption. If this value is below 8 kJ/mol, the adsorption type can be explained by physical adsorption; if it is between 8 and 16 kJ/mol, the adsorption type can be explained by ionic exchange; if it is between 20 and 40 kJ/mol, it can by explained by chemical adsorption [29]. In this study, the value of Ea for ISX was found to be 15.66 kJ/mol, suggesting that the adsorption of Cu(II) onto ISX was typically an ionic exchange process; the values of Ea for CSAX was 9.01 kJ/mol, which is near to the limit value with 8 kJ/mol of ionic exchange and physical adsorption, implying that the adsorption of onto CSAX involved both ion exchange and physical adsorption. These conclusions was in agreement with the above analysis of the concentration changes of Cu and Na.

Through the above analysis, CSAX had the adv-antages of the low adsorbent dosage and high ads-orption capacity while ISX had a higher removal effi-ciency and faster adsorption rate even though the optimum dosage of ISX was three times as much as that of CSAX. It should be noted that the production cost of CSAX was relatively high due to the grafting copolymerization and its post-processing treatment, so ISX seemsto be a much better adsorbent com-pared to CSAX as far as the removal of Cu(II) was concerned.

Treatment of water containing both turbidity and copper ions

The original concentration of Cu(II) in copper solution was 30 mg/L, and the adsorption experiment was carried out at room temperature and pH with 5.3. A certain dosage of kaolin suspension was added in the test solution with the turbidity of 100 NTU. Differ-ent dosages of ISX and CSAX were added in the test-ing solutions, respectively, and the results are shown in Figure 6. TR is defined as the turbidity removal when water sample contains only turbidity (100 NTU); CRt is defined as the copper ions removal when water sample contains both turbidity (100 NTU) and copper ions (30 mg/L); CR is defined as the copper ions rem-oval when water sample contains only copper ions (30 mg/L).

It was favorable for Cu(II) removal in the pre-sence of kaolin suspension, and the effect was imp-roved evidently with the increase of CSAX’s dosage. The removal efficiency of Cu(II) was up to 96.98% and turbidity removal was 98.28% at the dosage of 50 mg/L. Copper removal efficiency was much higher than the efficiency of 94% for the sample which only contained copper ions.

The major mechanisms of flocculation by poly-mers are charge neutralization and bridging. For neut-ral or anionic flocculants, flocculation is caused mainly by polymer bridging [39-41]. The suspended particulates of kaolin in the testing solution were floc-culated by PAM chains on the CSAX polymer due to a large amount of –CONH2 groups in CSAX, and the floc had the “sweep” function for the insoluble colloidal chelate compounds of copper with CSAX and had the weak adsorption function for soluble copper ions. Moreover, some of its groups would be adsorbed at the particle surface when a CSAX polymer came into contact with a colloidal particle, and the remainder of

0 50 100 150 200 250 30075

80

85

90

95

100

Rem

oval

rate

(%)

dosage (mg/L)

CR with CSAX TR with CSAX CRt with CSAX CR with ISX TR with ISX CRt with ISX

Figure 6. Treatment of water samples containing both turbidity and Cu(II) with ISX and CSAX.


474

the molecule (some xanthate groups) stretched into the solution. Adsorption can occur if residual Cu(II) in the solution contacted these extended segments by forming a particle–polymer–chelate compound com-plex [42]. Furthermore, kaolin itself can work as ads-orbent and can remove partially the Cu2+ from water medium even without the addition of polymer [43]. Therefore, CSAX had good flocculation performance, and the flocculation greatly improved the removal per-formance of Cu(II).

ISX’s removal efficiency of Cu(II) did not change obviously when both turbidity and copper ions con-tained in water sample. The maximum removal effi-ciency was still 99.5% and the maximum removal turbidity efficiency was 86% when the dosage was 150 mg/L, as same as that of the water sample which contained only Cu(II). This was much lower than that of CSAX. Because ISX only had starch chain as the bridging unit, it was less effective than PAM chains for removing turbidity.

CSAX was much more effective than ISX for removing turbidity and little less effective than ISX for removing Cu(II) when water sample contains turbidity and Cu(II). Therefore, CSAX has some certain advan-tages in treating toxic metals effluent which contains both heavy metals and turbidity.

Table 4. Comparison of maximum sorption capacity of other xanthated sorbents

Adsorbent Qmax / mg g-1 Reference

Orange peel xanthate 77.60 [44]

Xanthated sugarcane bagasse 2.91 [45]

Xanthate-modified magnetic chitosan

34.5 [46]

Cross-linked xanthate chitosan 43.47 [47]

ISX 466.877 This study

CSAX 2229.856 This study

Table 4 lists a comparison of maximum ads-orption capacity of Cu(II) with various xanthate ads-orbents. It can be seen that ISX and CSAX have much higher adsorption capacity of 466.877 and 2229.856 mg/g for Cu(II), indicating that they have a significant potential for removal of Cu(II) from aque-ous solutions.

CONCLUSIONS

In summary, based on the results of the present comparative investigation between ISX and CSAX, following conclusions were obtained.

1) Both ISX and CSAX can remove Cu(II) from aqueous solutions. The removal efficiency of Cu(II)

onto CSAX was determined by the contents of N and S while that of ISX was only related with the content of S. The absorption capacity of CSAX was much bigger than that of ISX while the removal efficiency of ISX was higher than CSAX.

2) The adsorption efficiency of Cu(II) onto CSAX and ISX increased with the increased dosage. Their adsorption kinetic process was well predicted by the pseudo-second-order model. Their equilibrium ads-orption data fitted well with the Freundlich and D–R isotherm models, and the 1/n value for Freundlich isotherm showed that Cu(II) were favorably adsorbed by the CSAX or ISX.

3) The physical process and ions exchange pro-cess both contributed to the adsorption of Cu(II) onto CSAX, whereas the adsorption mechanism of Cu(II) for ISX was mainly the ion exchange.

4) Turbidity was favorable for the Cu(II) removal by CSAX. CSAX seems to be a worthwhile alternative to the traditional ISX in the process of treating wastewater containing both copper ions and turbidity.

Acknowledgements

This work was financially supported by the Sci-ence and Technology Plan Projects of Jiaxing City, China (NO.2014AY21008), the Hi-Tech Research and Development Program of China (No. 2012AA06A304), the Platform Funds from Zhejiang Province (No. 2012F10028), the Research Project for Application of Public Technology of Zhejiang Province of China (No. 2012C31028), and the research funds from Nanhu College of Jiaxing University (No. N41472001-3).

REFERENCES

[1] P.X. Sheng,Y.P. Ting, J.P. Chen, L. Hong, J. Colloid Interface Sci. 275 (2004) 131-141

[2] W.S.W. Ngah, M.A.K.M. Hanafiah, Bioresour. Technol. 99 (2008) 3935-3948

[3] H.Y. Xu, L. Yang, P. Wang, Y. Liu, M. Peng, J. Environ. Manage. 86 (2008) 319–328

[4] T.A. Kurniawan, G.Y.S. Chan, W.H. Lo, S. Babel, Sci. Total Environ. 366 (2006) 409-426

[5] S.S. Banerjee, D.H. Chen, J. Hazard. Mater. 147 (2007) 792-799

[6] M.A. Shannon, P.W. Bohn, M. Elimelech, J.G. Georgi-adis, B.J. Marinas, A.M. Mayes, Nature. 452 (2008) 301- -310

[7] S.E. Bailey, T.J. Olin, R.M. Bricka, D.D. Adrian, Water Res. 33 (1999) 2469-2479

[8] G. Crini, Prog. Polym. Sci. 30 (2005) 38-70

[9] T.S. Anirudhan, S. Rijith, Colloids Surfaces, A. 351 (2009) 52-59

[10] D. Zhou, L.N. Zhang, J.P. Zhou, S.L. Guo, Water Res. 38 (2004) 2643-2650


475

[11] W.S.W. Ngah, S. Fatinathan, Chem. Eng. J. 143 (2008) 62-72

[12] G. Guclu, G. Gurdag, S. Ozgumus, J. Appl. Polym. Sci. 90 (2003) 2034-2039

[13] Q.F. Yin, B.Z. Ju, S.F. Zhang, X.B. Wang, J.Z. Yang, Carbohyd. Polym.72 (2008) 326-333

[14] K. Baek, J.S. Yang, T.S. Kwon, J.W. Yang, Desalination 206 (2007) 245-250

[15] S. Pal, D. Mal, R.P. Singh, Carbohyd. Polym. 59 (2005) 417-423

[16] W.E. Rayford, R.E. Wing, W.M. Doane, J. Appl. Polym. Sci. 24 (1979) 105-113

[17] R.E. Wing, W.M. Doane, C.R. Russell, J. Appl. Polym. Sci. 19 (1975) 847-854

[18] R.E. Wing, W.E. Rayford, W.M. Doane, C.R. Russell, J. Appl. Polym. Sci. 22 (1978) 1405-1416

[19] R.E. Wing, C.L. Swanson, W.M. Doane, C.R. Russell, J. Wat. Pollut. Control Fed. 46 (1974) 2043-2047

[20] Q. Chang, X.K. Hao, L.L. Duan, J. Hazard. Mater. 159 (2008) 548-553

[21] X.K. Hao, Q. Chang, X.H. Li, Appl. Polym. Sci. 112 (2009) 135-141

[22] X. Hao, C. Chang, L. Duan, Y. Zhang, Starch-Starke. 59 (2007) 251-257

[23] K.R. Nolan, J. Orthomol Med. 12 (1983) 270-282

[24] A.Q. Dong, J. Xie, W.M. Wang, L.P. Yu, Q.A. Liu, Y.P. Yin, J. Hazard. Mater. 181 (2010) 448-454

[25] J.C. Duan, Q. Lu, R.W. Chen, Y.Q. Duan, L.F. Wang, L. Gao, S.Y. Pan, Carbohydr. Polym. 80 (2010) 436-441

[26] J. Tan, X.Y. Wei, Y.X. Ouyang, J.H. Fan, R. Liu, Per. Pol. Chem. Eng. 58 (2014) 131-139

[27] W.M.D.R.E. Wing, US Patent 3979286 (1976)

[28] H. Chen, G.L. Dai, J. Zhao, A.G. Zhong, J.Y. Wu, H. Yan, J. Hazard. Mater. 177 (2010) 228-236

[29] I. Iwasaki, S.R.B. Cooke, J. Am. Chem. Soc. 80 (1958) 285-288

[30] M. Kostic, M. Radovic, J. Mitrovic,M. Antonijevic, D, Bojic, M. Petrovic,A. Bojic, J. Iran Chem. Soc. 11 (2014) 565– -578

[31] Y.S. Ho, G. McKay, Can. J. Chem. Eng. 76 (1998) 822- -826

[32] Y.S. Ho, G. McKay, J. Process. Biochem. 34 (1999)451- -455

[33] L. Guo, S.F. Zhang, B.Z. Ju, J.Z. Yang, Carbohydr. Polym. 63 (2006) 487-492

[34] L. Guo, G.Y. Li, J.S. Liu, Y.F. Meng, Y.F. Tang, Carbo-hydr. Polym. 93 (2013) 374-379

[35] S. Altenor, B. Carene, E. Emmanuel, J. Lambert, J.J. Ehrhardt, S.Gaspard, J. Hazard. Mater. 165 (2009) 1029- -1035

[36] I. Langmuir, J. Am. Chem. Soc. 40 (1918) 1361-1403

[37] H. Freundlich, Z. Phys. Chem. 57 (1906) 385-470

[38] W.S.W. Ngah, S. Fatinathan, J. Environ. Manage. 91 (2010) 958-969

[39] M. Boroumand Jazi, M. Arshadi, M.J. Amiri, A. Gil, J. Colloid Interface Sci. 422 (2014) 16-24

[40] A. Pourjavadi, S.M. Fakoorpoor, S.H. Hosseini, Carbo-hydr. Polym. 93 (2013) 506-511

[41] Y. Zhen, W. Hu, Y. Bo, H. Mu, Y. Hu, Chem. Eng. J. 244 (2014) 209-217

[42] Y.Zhen, H.J. Li, Y.Han, W.Hu, Y.Hu, Q. Wu, H.b. Li, J. Hazard. Mater. 276 (2014) 480-488

[43] N. Kutsevol, T. Bezugla, M. Bezuglyi, M. Rawiso, Macro-mol. Symp. 317 ( 2012)82-90

[44] N.C. Feng, X.Y. Guo, S. Liang, J. Hazard. Mater. 164 (2009) 1286-1292

[45] P.L. Homagai, K.N. Ghimire, K. Inoue, Bioresour. Technol. 101 (2010) 2067-2069

[46] B. Kannamba, K. Laxma Reddy, B.V. Appa Rao, J. Hazard. Mater. 175 (2010) 939-948

[47] Y.H. Zhu, J. Hu, J.L. Wang, J. Hazard. Mater. 221 (2012) 155-161.


476

JUN TAN1,2

XIAOYAN WEI1 YUXIA OUYANG1

RUI LIU2 PING SUN1,2

JUHONG FAN3 1Department of Chemical and Textile

Engineering of Nanhu College, Jiaxing University, Jiaxing, Zhejiang Province,

China 2College of Biological and Chemical

Engineering, Jiaxing University, Jiaxing, Zhejiang Province, China

3Zhejiang Provincial Key Laboratory of Water Science and Technology,

Department of Environment, Yangtze Delta Region Institute of Zhejiang, Jiaxing, Zhejiang Province, China

NAUČNI RAD

EVALUACIJA NERASTVORNOG KSANTATA I UMREŽENOG SKROBA SA KALEMLJENIM KOPOLIMEROM POLIAKRILAMIDA I NATRIJUM- -KSANTATA ZA ADSORPCIJU Cu(II) U VODENIM RASTVORIMA

U ovom radu je procenjena efikasnost nerastvornog ksantata (ISX) i umreženog skroba sa kalemljenim kopolimerom poliakrilamida i natrijum-ksantata (CSAX) za uklanjanje Cu(II) jona iz otpadnih voda. Dve vrste ksantata su okarakterisane elementarnom mikroanalizom, kao i SEM, XRD i FTIR metodama. Analizirani su i faktori koji utiču na adsorpcione karak-teristike jona bakra iz vodenog rastvora. Rezultati su pokazali da CSAX poseduje bolji adsorpcioni kapacitet za Cu(II) od ISX, s obzirom na to da sadrži više azota i sumpora. S druge strane, što se tiče efikasnosti izdvajanja Cu(II) jona, ISX je bolji od CSAX zbog sadržaja jakih –CSS grupa. Uklanjanje jona bakra kod obe vrste ksantata se povećava sa povećanjem pH rastvora. Mehanizam Cu(II) adsorpcije na ISX je jonska izmena, dok su jonska izmena i fizička adsorpcija odgovorne za adsorpciju kod CSAX. Kinetika adsorpcije kod oba adsorbenta odgovara modelu pseudo-drugog reda, a asdorpcione izoterme odgo-varaju Freundlich izotermama. Ispitivanje sa sintetičkim otpadnim vodama ukazuje na CSAX kao korisnu alternativu tradicionalnom ISX u slučaju kada otpadna voda sadrži i Cu(II) jone i zamućenje.

Ključne reči: nerastvorni skrobni ksantat, umreženog skroba sa kalemljenim kopolimerom poliakrilamida i natrijum-ksantata, uklanjanje Cu(II), kinetika ads-orpcije, adsorpciona izoterma.




477

OGBEMUDIA JOSEPH OGBEBOR1

FELIX EBHODAGHE OKIEIMEN2

DAVID EHIOGHILEN OGBEIFUN2

UZOMA NDUBUISI OKWU1

1Research Support Services Department, Rubber & Gum

Tech./Quality Control Division, Rubber Research Institute of

Nigeria, Benin City, Nigeria 2University of Benin, Department of Chemistry, Center for Biomaterials

Research, Benin City, Nigeria

SCIENTIFIC PAPER

UDC 666.321.09:678.4:544

DOI 10.2298/CICEQ140221003O

ORGANOMODIFIED KAOLIN AS FILLER FOR NATURAL RUBBER

Article Highlights • Increased interlayer spacings • ts2, t90, ML and MH were affected • High acceleration of cure at 2 and 4 phr loading • M300, TS and elongation at break improved • Abrasion resistance and IRHD showed similar trends like tensile properties Abstract

Organokaolin samples, through the incorporation of cationic hexadecyltri-methylammonium bromide in various concentrations (50, 100 and 200% cation exchange capacity, CEC) into kaolin clay’s interlayer spaces have been pre-pared. The samples were characterized using XRD and FTIR to get inform-ation on structural composition and characteristic bonds on modification. These clays were further used as fillers in natural rubber compounds with a semi-ultra-delayed action accelerator scheme. The X-ray diffraction analysis showed marginal increase in basal (d(001)) spacing of kaolin platelets from 4.01 to 4.90 nm. Changes in the clay’s molecular environment induced by ion--exchange process were followed by FTIR measurements revealing various CTAB+ influenced absorption peaks as modification progressed. Cure char-acteristics, scorch (ts2) and cure (t90) time of the organokaolin filled natural rub-ber composites were observed to be better than those of the 40 phr bulk kaolin across the CEC organophilization concentrations and filler loadings studied. Vulcanizate properties showed considerable increase in M100, M200, M300, TS and elongation at break (%) indicating its potential as an organomodified filler. Hardness (IRHD) and abrasion resistance showed similar trend as tensile properties, with the incorporation of organoclay.

Keywords: organokaolin, hexadecyltrimethylammonium bromide, organo-philization, X-ray diffraction, cure properties, vulcanisate properties.

Clays are important raw materials, with esti-mated consumption of over 1,600,000 t consumed as fillers [1]. They have found uses in the polymer, paint, paper, etc. industries as non-black fillers [1,2]. Clays are natural minerals comprising of certain groups of hydrous aluminum, magnesium and iron silicates that may contain sodium, calcium, potassium, and other ions. These silicates are called the clay minerals, the major clay mineral groups are kaolins, smectites, illi-tes, chlorites and hormites. Kaolins are used to great-

Correspondence: O.J. Ogbebor, Research Support Services Department, Rubber & Gum Tech./Quality Control Division, Rubber Research Institute of Nigeria, Benin City, Nigeria. E-mail: [email protected] Paper received: 21 February, 2014 Paper revised: 9 January, 2015 Paper accepted: 27 January, 2015

est extent (54%) when compared to other non-black fillers. They are used as non-black fillers in polymers to cheapen and modify processing by reducing nerve in shaping operations and ensuring dimensional stab-ility in unvulcanized stocks at high loadings > 40 wt.% [3]. Kaolins have also been used to aid smooth plastic surface, improve electrical resistance in wire and cable coatings and helps control flow properties in polishing compounds [4]. Recently, organomodified clays emerged as novel class of reinforcing fillers for the reinforcement of polymers. A unique feature of these materials is their ability to impart a rare com-bination of properties to the base polymer at low load-ings < 10 wt. % [4,5]. This means that superior per-formance can be realized with significant weight savings. These composites are developed through

O.J. OGBEBOR et al.: ORGANOMODIFIED KAOLIN AS FILLER… Chem. Ind. Chem. Eng. Q. 21 (4) 477−484 (2015)

478

either in situ polymerization, direct solution intercal-ation of the organically modified layered silicate, or melting intercalation into the polymer matrix.

Organic modification intercalates are formed when clay is put in aqueous surfactant solutions, for example quaternary ammonium surfactants having long hydrocarbon chain, e.g., hexadecyltrimethyl-ammonium bromide, CTAB, etc. This leads to an inc-rease in interlayer spacing, which can be estimated by X-ray diffraction (XRD) [5-10]. Also, the extent of swelling of clay is said to be dependent on the length of the alkyl chain and the cation exchange capacity (CEC) [12]; hence, the choice of surfactant could facilitate the level of modification of kaolin clay mate-rial. A review of literature on organomodified filler-polymer composites showed that montmorillonite (bentonite) has been studied extensively [5–13]. But as the natural deposits of montmorillonite minerals are rather limited and the demand for bentonites ever increasing, there has been considerable interest in finding substitute mineral. In this context, only limited information is available with the relatively less expen-sive and abundantly available mineral like kaolin

[14,15]. Kaolin consists chiefly of the mineral kaolinite and is abundantly available. Its low cost encourages its industrial utility.

Kaolinite [Al4Si4O10(OH)8] is a dioctahedral alu-minosilicate, 1:1 layered clay mineral, built with a tetrahedral SiO4 sheet and an octahedral AlO4(OH)2 sheet linked together by oxygen atoms. The crystal consists of several of these layers extending in a two-dimensional array, which are stacked along the c-axis and held together essentially by: i) hydrogen bonds between the external hydroxyls of the octahedral sheet and the basal oxygen of the adjacent layer tetrahedral sheet, ii) van der Waals attractive forces, and iii) electrostatic interactions due to net fractional charges of opposite sign on each basal surface. Although, the surface silicate sheet of kaolinite is not usually amenable to covalent attachment, the rela-tively reactive aluminol surface is similar to that in the case of montmorillonopkites and has the potential to be functionalized via Al–O–R bonds. Organoclays are particularly explored as matrix-reinforcing compo-nents for their high aspect ratio, plate morphology, natural availability and low cost to develop [14]. There is however, a dearth of information in the literature on organic modification intercalates developed from kao-lin in clay-aqueous surfactant solutions unlike mont-morillonite. In view of the foregoing, this study exam-ines 50, 100 and 200% CEC modification of hexa-decyltrimethylammonium bromide on the basal spac-ing of kaolin using X-ray diffraction (XRD), its effects

on composition, structure, characteristic bonds on the clay’s molecular environment observed using Fourier Transform Infrared Spectroscopy (FTIR). The modified clays were then applied as fillers in natural rubber compounds in a semi-ultra-delayed action accelerator, and filler (2, 4, and 8 phr) effects on cure and mechanical properties of the natural rubber compounds were evaluated.

EXPERIMENTAL

Clay samples were collected from exposed faces of deposit situated on long. 06°39'5.3" E and lat. 6°13'39.2" N, purified by water washing through 75 µm mesh size and its composition (by weight was: SiO2 32.11%, Al2O3 21.40%, TiO2 4.30%, Fe2O3 1.72%, K2O 0.64%, MgO 6.48%, CaO 15.20%, Na2O 0.56%. The modification of clay with hexadecyltri-methylammonium bromide (CTAB) was carried out using the procedure: 1.5 g of purified clay dispersed in 94 ml of distilled water, stirred with magnetic stirrer for about 3 hrs at 80 °C. 0.5 g of hexadecyltrimethyl-ammonium bromide (C4H9N

+ (CH2CH2OH)2Br) was dissolved in a mixture of distilled water and concen-trated hydrochloric acid (35%) at 80 °C with 1 h of stirring. The pre-dissolved intercalating agent was then added to the clay suspension at 80 °C. The concentrations of the intercalating agent were in 50, 100 and 200% CEC of the clay. The reaction mixtures were stirred vigorously for 1 h at 80 °C. This was then washed copiously with water until filtrate was about pH 7, and dried at 70 °C for 24 h and ground in a mortar and stored in vacuum desiccators for five days before analysis [6]. XRD of samples was carried in a monochromatic MD 10 mini-diffractometer, with Ni-filter CuKα radiation in the 2θ region of glancing angle 15-75° and automatic silt. All recordings were taken at room temperature. The spacing was cal-culated using Bragg’s Wulf equation, nλ = 2d sinθ, where λ is the wavelength of monochromatic X-ray source, d is the spacing between two similar planes, θ is the angle at which X-ray falls on the sample, and n is the order of reflection. IR spectroscopy is used in order to give information as far as composition of a sample, its structure and its characteristic bonds are concerned. In addition, IR spectroscopy is applied on clay minerals in order to study the nature of isomor-phic substitutions of cations in octahedral and tetra-hedral sheet of the lattice and the degree of crys-tallinity. IR was carried out on the clay samples using an FTIR machine in a universal demountable cell and scanned at a range of 350–4000 cm-1 using the Spec-trum BX system (Perkin–Elmer, England).


479

Preparation of compounds

Mixes were prepared as in a laboratory two roll mill (Banbury-Pullen, model, 35100). The mill opening was set at 1.4 mm, and the initial temperature was set at 80±5 °C. The mixing involved two stages of oper-ation. The first step features an initial banding of nat-ural rubber on the front roll of the two-roll mill, fol-lowed by ¾ cuts on both sides of the band, followed by adding half content of organokaolin, then zinc oxide, stearic acid, paraffin oil and wax, allowed to mix properly for 5 min. This was followed by the incorporation of the remaining ingredients and 6PPD for a further 3.5 min. In the final step, the addition of accelerator and vulcanizing agents (CBS and sulphur) for 2.0 min was done after the stock was allowed to cool to 70 °C, as shown in Table 1. The rheological behavior of the rubber compounds was determined on Alpha oscillating disc rheometer (ODR 2000) using a 1° rotor oscillating amplitude and frequency 50 Hz [16]. The cure rate index (CRI) and other parameters of cure were estimated from the obtained rheographs. Tensile specimens were cut from the moulded sheets, according to BS 903, Part A2 (DIN 53504) [17]. Ten-sile properties: M100, M200, M300, tensile strength and elongation at break (%) were determined at room temperature on a Zwick/Roell Z005 testing machine with crosshead speed of 200 mm/min. The abrasion test was carried out in accordance to BS 903, Part A9 [18], consisting of a trial run, a running-in period and five test runs. Absolute value of abrasion was the mean value calculated from the five test runs expres-sed in mg per 1000 revolutions of the abrasive wheel. Hardness tests of the rubber vulcanizate were deter-mined in accordance to BS 903 (ISO 7619) [19], with an international rubber hardness tester.

Table 1. Formulations for investigated organokaolin filled nat-ural rubber compounds; 6PPD: N-(1,3-dimethylbutyl)–N’-phenyl-p-phenylenediamine; CBS: N-cyclohexyl-2-benzothiazole sul-fonamide

Compound component Parts hundred rubber (phr)

Natural rubber 100 100 100 100 100

Paraffin oil 10 10 10 10 10

Organomodified kaolin 0 2 4 8 -

Bulk kaolin - - - - 40

Zinc oxide 10 10 10 10 10

Stearic acid 2 2 2 2 2

6PPD 1.5 1.5 1.5 1.5 1.5

Wax 1.5 1.5 1.5 1.5 1.5

CBS 0.6 0.6 0.6 0.6 0.6

Sulphur 2.8 2.8 2.8 2.8 2.8


X-ray diffraction was used to observe the clay materials before and after modification with CTAB. The XRD of bulk clay and modified clays are depicted in Figure 1. The interaction between kaolin clay and CTAB organic compound resulted in a shift of the d-spacing d(001) towards lower 2θ values of the kaolin clay material implying the expansion of the interlayer spaces due to the surfactant. Table 2 shows the var-ious glancing angles 2θ and d(001) spacing of the unmodified kaolin and the modified kaolin at 50, 100 and 200% CEC, respectively. While unmodified kaolin is 4.01 nm, those modified show increased d-spacing as modification progressed, hence 4.37, 4.46 and 4.90 nm for 50, 100 and 200% CEC modifications. The interaction between the clay and the surfactant led to the observed changes in the d-spacing, imply-ing the expansion of the interlayer space due to the alkylammonium intercalation. Basal spacings reflect the proportion of the interlayer occupied by the amphiphilic substances. For this reason, the gallery spacing gradually increases, depending on the amount of CTAB interacted with the layered silicate [20]. Also, depending on the alkylammonium packing density and alkyl chain length (CTAB+), the carbon chain can

Figure 1. XRD diffractograms showing: A – bulk kaolin, B – 50% CEC-CTAB kaolin, C – 100% CEC-CTAB kaolin and D – 200%

CEC-CTAB kaolin.


480

be arranged in the kaolin interlayer spaces, forming either monolayers or bilayers parallel to the clay sur-face [11]. These changes in arrangements are detected in the clay basal spacing.

Table 2. Glancing angles (2θ) and interplanar spacings, d, of X-rays reflections from lattices of organokaolin

Kaolin Organokaolin

50% 100% 200%

2θ / ° d / nm 2θ / ° d / nm 2θ / ° d / nm 2θ / ° d / nm

36.06 4.01 25.21 4.37 19.87 4.46 18.09 4.90

43.45 3.48 26.44 3.35 20.37 3.36 18.87 4.70

45.57 3.27 26.97 3.30 25.27 3.52 19.73 4.50

49.95 2.49 36.95 2.43 26.38 3.37 22.45 3.95

55.33 2.32 38.44 2.34 27.04 3.29 23.30 3.81

57.81 1.83 38.87 2.31 36.45 2.46 25.06 3.55

62.92 1.66 39.55 2.27 38.79 2.32 33.33 2.68

63.42 1.48 39.80 2.26 39.58 2.27 35.06 2.55

FTIR spectra of bulk and modified clay are shown in Figure 2. Table 3 shows the absorption

peaks in cm-1 of these clay materials. Knowledge of organoclay characteristics is essential to optimizing the applications of the materials. Especially in the case of polymer-clay composites, the mechanism that controls the clay dispersibility into the polymer matrix is related to these characteristics and is of fundam-ental importance in the design of materials with desired properties [21]. These spectra reveals that as modification with CTAB+ progressed the absorption peaks increased with accompanied broadening and shift of absorption positions, changes in band con-tours associated with changes in the isomorphic sub-stitutions of the cations in the octahedral and tetra-hedral sheet of the clay lattice. Furthermore, matching the absorption peaks with infrared spectroscopy cor-relation table [22,23], the changes in the clay mole-cular environment lead to peaks of 1652 cm-1 of the bulk clay to absorption peaks 3434, 3457 and 3667 cm-1 for the 100 and 200% CEC-CTAB modifications, indicating a growing presence of amide (CONH2), amine (NH2C, CNHC and CNCC), etc. groups with

Figure 2. FTIR Spectra of: A – bulk kaolin, B – 50% CEC-CTAB kaolin, C – 100% CEC-CTAB kaolin, D – 200% CEC-CTAB kaolin.

Table 3. FTIR absorption peaks (cm-1) of organokaolin samples

Bulk kaolin 1652, 1036, 925, 683, 547, 458

50 % CEC-CTAB kaolin 1646, 1038, 928, 680, 548, 458

100% CEC-CTAB kaolin 3667, 3457, 2348, 1638, 1032, 925, 677, 539, 444

200% CEC-CTAB kaolin 3667, 3434, 2931, 2348, 1934, 1823, 1638, 1475, 1037, 925, 669, 542, 432


481

pronounced multiple broad peaks, which are asso-ciated with ammonium ion absorption because of N–H stretching vibrations. The 2348 cm-1 characteristic of strong NH3

+ stretching band was observed in the 100 and 200% CEC-CTAB clay, with an additional 2931 cm-1 strong absorption NH3

+ stretching band in 200% CEC-CTAB clay. The overlap aliphatic amine of 1032 cm-1 and conjugation C=O effects 1638 cm-1 absorp-tion were also noticed in the 100% CEC-CTAB clay, whereas the 1823cm-1 absorption peak for acyl halide (C–Br), 1638cm-1 (C=O effects), 1475 cm-1; strong pri-mary amine (N–H), and 1037 cm-1 (overlap aliphatic amine) were noticed in the 200% CEC-CTAB clay spectrum. The 539, 542 and 677 cm-1 absorption peaks were indicative of the presence of bromoalka-nes (C–Br) whereas the 925 cm-1 of 200% CEC-CTAB clay was C=CH, vinyl bond type presence. However, the 1934 cm-1 of 200% CEC-CTAB clay was not avail-able in the spectroscopy tables used (this will be inv-estigated in subsequent studies).

In design of rubber products formulation, two of the most critical properties of rubber and rubber com-pounds are processibility and vulcanization. These characteristics are vitally important because they define the operating window available for converting uncured rubber compound into a usable product. The processibility of stock can be followed by monitoring cure properties of rubber compounds. Cure properties of natural rubber compounds containing unmodified and modified clay material are given in Table 4. Scorch time, ts2, increased from 2.9, through 3.7 and 3.8 min at 2 phr filler of the 50, 100 and 200% CEC level of modification. The 4 phr indicates 2.8 min, 3.3 min, and 3.3 min at 50, 100 and 200% modifications respectively. At 8 phr loadings, it was 3.7, 3.2 and 3.0 min for the 50, 100 and 200% CEC modifications. Scorch is a valuable assessment of the compounding

recipe as it indicates compounds processing safety. The various organokaolin composites show better scorch time when compared to that of the control bulk clay at loading of 40 phr, which indicated 2.2 min. Cure time (t90) as depicted in Table 4 on the other hand is the time required during the vulcanization for crosslinking to occur, yielding the desired level of pro-perties can be seen to be generally better for most of the organokaolin composites across the CEC concen-trations than that of the 40phr bulk clay (control filler level). This acceleration of cure as a result of the increased presence and interaction of the organo-kaolin with natural rubber polymer was also observed in the study of Lopez-Manchado et al. [11] on sub-stituting carbon black with organomontmorillonite in NR compounds and Teh et al. [24] on natural rub-ber/organoclay nanocomposites compatibilized with epoxidized natural rubber. The absolute torque level, Tmax, increased as the organokaolin loading increased with modification % increase, indicating a gradual inc-rease of crosslinking (resulting in the compound changing from a soft plastic to a tough elastic material required for its end use) as organokaolin increased. The torque maximum (MH) increased across the filler levels 2, 4, and 8 phr and the 50, 100 and 200% CEC-CTAB modifications. This increase in viscosity could have been encourage by heat, which led to exfoliation of the polymer in the presence of the orga-nokaolin as a result of the growing presence of the CTAB+ in the clay platelets, thereby improving inter-actions of the rubber molecules with clay leading to improved properties. It is known that the amount of bound rubber on reinforcement increases due to mechanical breakdown of polymer chain molecules and results in free radicals formation at newly formed chain ends; these becomes reactive sites for the filler surface and these free radicals from the polymer

Table 4. Cure properties at 150 ºC of organokaolin filled natural rubber compounds; Tmax: absolute torque level (T90+ML), ML: torque minimum, MH: torque maximum, CRI: cure rate index, 100/(t90–ts2)

Parameter

Filler loading, phr

0 2 2 2 4 4 4 8 8 8 40

CEC-CTAB level, %

0 50 100 200 50 100 200 50 100 200 -

ts1 / min 2.3 2.4 3.5 3.7 2.7 3.2 3.3 3.0 3.0 3.5 2.2

ts2 / min 2.5 2.9 3.7 3.8 2.8 3.3 3.3 3.7 3.2 3.0 2.6

t90 / min 4.4 4.6 5.0 5.6 4.3 5.7 5.5 5.2 5.8 6.0 4.6

Tmax 6.5 6.7 6.9 8.0 6.6 8.2 8.3 7.4 8.1 8.8 14.5

CRI 52 56 63 53 51 45 46 59 79 89 56

ML / kg cm3 2.1 2.1 1.9 2.4 2.3 2.5 2.8 2.2 2.3 2.8 10.1

MH / kg cm3 27 30 31 32 32 34 36 34 36 40 36.4

MH-ML 24.8 27.9 29.2 30 29.8 31.5 33 31.8 33.4 36.7 26.4


482

result in bound rubber. Since there are many sites on a filler particle, it then acts as a giant crosslink. This bound rubber, when considered as part of the volume occupied by the filler, influences the hydrodynamic properties such as viscosity of the rubber.

Table 5 gives the tensile properties; M100, M300, tensile strength and elongations at break of the various investigated organokaolin in natural rubber compounds. As expected M100, M300 and tensile strength, TS in MPa indicated reasonable increase as the filler level (2, 4 and 8 phr) and CEC-CTAB (50, 100 and 200%) modifications were compared to the unfilled compound and the 40 phr natural rubber com-pounds respectively. At 2 phr the M100 were 50%; 1.4 MPa, 100%; 1.8 MPa and 200%; 3.3 MPa as against the 0.9 MPa of the unfilled and 1.3MPa of 40 phr bulk clay in natural rubber compounds. Similar increase was also observed at loadings of 4 phr: 50%; 1.7 MPa, 100%; 1.9 MPa, 200%; 3.6 MPa and 8 phr: 50%; 2.2 MPa, 100%; 2.8 MPa and 200%; 4.1 MPa. The increase in tensile modulus may be considered as a direct indication of the reinforcing effect of orga-nokaolin filler. This can be taken as the dispersibility effect of the organokaolin in the NR matrix. Organo-clay platelets have been reported to possess high aspect ratios [24] and thus act as good reinforcing elements, taking into cognizance a good filler-rubber interaction. The ammonium intercalant hexadecyltri-methylammonium bromide of the organoclay likely facilitates the disintegration of the layered clay par-ticles. The resulting exfoliations improved mechanical properties. Similarly, increase in tensile modulus has been reported for different NR hybrids containing low dosages of organomodified montmorillonite clays [8,11,14,24]. At M300, which is 300% strain and a measure of stiffness of rubber composites were at 2 phr: 50, 100 and 200% – 3.6, 4.2 and 5.1 MPa, and 4

phr: 50, 100 and 200% – 3.2, 4.4 and 5.4 MPa and 8 phr: 50, 100 and 200% – 3.9, 4.9 and 6.8 MPa, indi-cating an increase with filler content and polymer exfoliation. Elongation at break (%) of the natural rubber composites were observed to become low as filler levels and modification concentrations increased across the studied compounds when compared to the unfilled and 40 phr of bulk clay. This is believed to be due to the exfoliation of the polymer with the organo-kaolin that causes higher crosslinking of the rubber in the neighborhood of the organoclay platelets [25]. The increment in crosslinking resulted in a reduction in elongation at break. The reduction in elongation is believed to be caused by an increasing tendency for clay agglomeration as filler loading increase [8]. Hard-ness (IRHD) increased as the tensile properties inc-reased. Abrasion (mg/1000 rev.) also increased as the loading level and the CEC-CTAB modification concentrations increased. This increase is also anal-ogous to that reported for NR organocomposites con-taining onium ion modified montmorillonite [24] and montmorillonite modified with octadecylamine [26]. The reinforcement effect of CTAB modified kaolin clay as evidenced by the increase in tensile modulus, ten-sile strength, hardness and abrasion may be exp-lained by the possible formation of structure between organokaolin and NR. It is quite possible that there are interactions between the cations and silanol hyd-roxyl groups of kaolin and the ammonium (NH4

+) of CTAB resulting in sufficient intercalation of the addi-tive between the clay platelets. This, in turn, could increase the hydrophobicity of kaolin leading to further polymer (natural rubber) exfoliating effect that could result in the observed reinforcing effect in the natural rubber compounds studied.

Table 5. Mechano-physical properties of organokaolin filled natural compounds; EB: elongation at break; IRHD: international rubber hardness degrees

Parameter

Filler loading, phr

0 2 2 2 4 4 4 8 8 8 40

CEC-CTAB level, %

0 50 100 200 50 100 200 50 100 200 -

M100 / MPa 0.9 1.4 1.8 3.3 1.7 1.9 3.6 2.2 2.8 4.1 1.3

M300 / MPa 2.3 3.6 4.2 5.1 3.2 4.4 5.4 3.9 4.9 6.8 1.8

TS / MPa 14.2 22.4 26.4 32.2 23.3 28.5 37.4 28.4 34.8 42.4 18.2

EB / % 321 256 229 233 201 196 185 270 245 178 265

IRHD 41 43 44 46 47 48 49 51 54 56 55

Abrasion, mg/1000 rev. 0.29 0.34 0.35 0.37 0.45 0.46 0.48 0.40 0.45 0.52 1.52

M100 / MPa 0.9 1.4 1.8 3.3 1.7 1.9 3.6 2.2 2.8 4.1 1.3

M300 / MPa 2.3 3.6 4.2 5.1 3.2 4.4 5.4 3.9 4.9 6.8 1.8


483

CONCLUSION

Kaolin clay has been modified using hexadecyl-trimethylammonium bromide (cationic surfactant) at 50, 100 and 200% CEC concentrations, resulting in organokaolin. From the study, XRD reveals there was an increase in basal spacing between the clay layers because of intercalation. FTIR spectra show inc-reasing absorption peaks arising from the effects of the CTAB+ on the kaolin clay platelets. Rheological analysis shows that kaolin has potential in the org-anomodification quest, as CTAB-kaolin imparted reasonably on the cure properties of natural rubber composites studied. The organokaolin gave rise to higher degree of crosslinking as a result of polymer chain exfoliation, thereby resulting in the considerable increase in mechano-physical properties, which were observed across the CEC concentrations. The results above have shown that the surfactant treatment of the kaolinitic silicate allows the dispersion of silicate layers into the matrix of NR and improves the filler- -matrix compatibility and hence improved natural rub-ber compound properties.

REFERENCES

[1] H.H. Murray, Clay Sci. 12 (2006) 106-112

[2] H.H. Murray, in E. Dominguez, G. Mas, F. Gravers, Eds., A Clay Odessey, Elsevier, Amsterdam, 2003, pp. 3-10

[3] N.G. McCrum, C.P. Buckley, C.B. Bucknall, Principles of Polymer Engineering, Oxford Univ. Press, New York, 2010, p. 283

[4] H.H. Murray and J.E. Kogel, Appl. Polym. Sci. 29 (2005) 199-206

[5] A.K. Kulshreshtha, A.K. Maiti, M.S. Choudhary, K.V. Rao, J. Appl. Polym. Sci. 99 (2006) 1004-1009

[6] B. Zidelkheir, M. Abdelgoad. J. Therm. Anal., Calorim. 94 (2008) 181-187

[7] M.S. Bakshi, R. Sood. Physiochem. Eng. Aspects 233 (2004) 203-210

[8] R. Alex, C. Nah. J. Appl. Polym. Sci. 102 (2006) 3277- -3285

[9] H. Yang, X. Zheng, W. Huang, K. Wu, Biointerfaces 65 (2008) 281-284

[10] L. Zhou, H. Chen, X. Jiang, F. Lu, Y. Zhou, W. Yin, X. Ji, J. Colloid interface Sci. 332 (2009) 16-21

[11] M.A. López-Manchado, M. Arroyo B. Herrero, Polymer 44 (2003) 2447-2453

[12] D.R. Paul, Q.H. Zeng, A.B. Yu, G.Q. Lu, J. Colloid interface Sci. 292 (2005) 462-468

[13] S.J. Ahmadi, C. G’sell, Y. Huang, N. Ren, A. Mohaddes-pour, J. Hiver. Comp. Technol. 60 (2009) 2566-2572

[14] R. Sukumar, A.R.R. Menon. J. Appl.Polym. Sci. 107 (2007) 3476-3483

[15] L.E. Yahaya, K.O. Adebowale, A.R.R. Menon, B.I. Olu- -Owolabi, Am. J. Mat. Sci. 2 (2012) 1-5

[16] ISO 3417 (2000-E) Rubber – Measurement of Vulcan-isation Characteristics Disc Rheometer

[17] British Standards Institute, BS 903; Part A2: Deter-mination of Tensile Stress-Strain Properties (DIN 53504)

[18] British Standards Institute, BS 903; Part A9: Deter-mination of Abrasion Resistance

[19] British Standards Institute, BS 903, Part A57: Deter-mination of Hardness (ISO 7619)

[20] A. Gürses, M. Ejder-Korucu, and Ç. Doğar, Sci. World J. (2012) 1-8

[21] P.C. LeBaron, Z. Wang, T.J. Pinnavaria, Appl. Clay Sci. 15 (1999) 11-18

[22] G. Socrates, Infrared and Raman characteristic Group frequencies: Tables and charts, John Wiley and Sons, New York, 2004, p. 18

[23] P. Larkin, Infrared and Raman Spectroscopy: Principles and Spectral Interpretation. Elsevier, Amsterdam, 2011, p. 5

[24] P.L. Teh, Z.A. Mohd Ishak, A.S. Hashim, J. Karger- -Kocsis, U.S. Ishiaku. J. Appl. Polym. Sci. 100 (2006) 1083-1092

[25] R.S. Peila, G. Lengvinaite, Malucelli, A.Priola, S. Ronchetti, J.Therm. Calorim. 91 (2008) 107-111

[26] A. Mousa, J. Karger-Kocsis, Macromol Mater. Eng. 286 (2001) 260-266.


484

OGBEMUDIA JOSEPH OGBEBOR1

FELIX EBHODAGHE OKIEIMEN2

DAVID EHIOGHILEN OGBEIFUN2

UZOMA NDUBUISI OKWU1 1Research Support Services Department, Rubber & Gum

Tech./Quality Control Division, Rubber Research Institute of Nigeria, Benin

City, Nigeria 2University of Benin, Department of Chemistry, Center for Biomaterials

Research, Benin City, Nigeria

NAUČNI RAD

ORGANO-MODIFIKOVANI KAOLIN KAO PUNILAC PRIRODNOG KAUČUKA

U radu je pripremljen organokaolin, postupkom inkorporiranja katjonskog heksadeciltri-metilamonijum-bromida u različitim koncentracijama (sa kapacitetom katjonske izmene 50, 100 i 200%, CEC) u međuslojeve kaolinske gline. Karakterizacija dobijenog kaolina je izvr-šena korišćenjem XRD i FTIR metoda, da bi se dobila informacija o strukturi uzorka i karakterističnim vezama koje se formiraju pri modifikaciji. Ovako dobijena glina je dalje korišćena kao punilac prirodnog kaučuka po šemi odloženog delovanja polu-ultra akce-leratora. XRD analiza pokazuje marginalno povećanje u bazalnom (d(001)) razmaku pločica od 4.01 do 4.90 nm. Promene u molekularnom okruženju gline, uslovljene jonskom izme-nom, praćene su FTIR analizom, uz uočavanje velikog broja CTAB+ absorpcionih pikova kao posledice same modifikacije. Svojstva umrežavanja, vreme pečenja (ts2) i umreža-vanja (t90) kompozita prirodnog kaučuka i organokaolina kao punioca su bila bolja od svoj-stava smeša kaolina i kaučuka (40 phr) u opsegu korišćenih kapaciteta jonske izmene i količine punioca. Osobine vulkanizata su značajno povećane kod M100, M200, M300, TS i istezanja kod prekida (%), što ukazuje na njegove značajne osobine kao organo modi-fikovanog punioca. Inkorporacija organogline utiče na tvrdoću i otpornost na abraziju u istom trendu kao i na zatezna svojstva.

Ključne reči: organokaolin, heksadeciltrimetilamonium-bromid, organofilizacija, X-ray difrakcija, svojstva umrežavanja, osobine vulkanizata.




485

VESNA M. PAVELKIĆ1

TANJA P. BRDARIĆ2

MARIJA P. PETROVIĆ3

GAVRILO M. ŠEKULARAC1

MILICA G. KOŠEVIĆ1

LATO L. PEZO4

MARIJA A. ILIĆ5

1Institute of Chemistry, Technology and Metallurgy, University of

Belgrade, Belgrade, Serbia 2Vinča Institute of Nuclear

Sciences, University of Belgrade, Belgrade, Serbia

3Institute "Kirilo Savić", Belgrade, Serbia

4Institute of General and Physical Chemistry, Belgrade, Serbia

5Faculty of Mining and Geology, University of Belgrade, Belgrade,

Serbia

SCIENTIFIC PAPER

UDC 66.093.48:634.13:544.4

DOI 10.2298/CICEQ141014004P

APPLICATION OF PELEG MODEL ON MASS TRANSFER KINETICS DURING OSMOTIC DEHYDRATATION OF PEAR CUBES IN SUCROSE SOLUTION

Article Highlights • Mass transfer kinetics during osmotic dehydration process of pears in sucrose solution

was studied • Peleg model was applied to the experimental data to describe sorption kinetics curves• The equilibrium values for moisture and solid content were estimated using Peleg

equation • Peleg rate constants for WL and SG at all temperatures followed an Arrhenius type

relationship Abstract

The applicability of Peleg model was investigated for predicting mass transfer kinetics during the osmotic dehydration (OD) process of pears, at different concentrations (40, 60 and 70%, w/w) and temperatures (20, 35 and 50 °C) of sucrose solution. Increase in sucrose solution concentration resulted in higher water loss (WL) and solid gain (SG) values through the osmotic treatment period. After 360 min of osmotic treatment of pears, WL ranged from 23.71 to 31.68% at 20 °C, from 24.80 to 40.38% at 35 °C and from 33.30 to 52.07% at 50 °C of initial weight of pears. The increase of dry mass of the samples, SG, after 360 min of osmotic treatment ranged from 3.02 to 6.68% at 20 °C, from 4.15 to 7.71% at 35 °C and from 5.00 to 8.92% at 50 °C. Peleg’s rate cons-tants, k1

WL and k1SG, decreased with increasing temperature, as well as dec-

reased with increasing concentration of osmotic solution at constant tempe-rature. Both capacity constants k2

WL and k2SG also exhibited the inverse rel-

ationship between capacity constant and temperature, as well as concentration of the osmotic solution. Peleg’s rate constants for WL and SG at all tempe-ratures followed an Arrhenius type relationship. The predicted equilibrium values were very close to experimental ones, which was confirmed with high coefficients of determination and by the residual analysis.

Keywords: osmotic dehydration, pears, kinetics, temperature effect, Peleg model.

The pear (Pyrus communis L.) is one of the most traditionally cultivated fruits, particularly in tem-perate climate zones in Europe. This fruit abounds in saccharides and dietary fiber as well as in nutritionally valuable compounds such as antioxidant flavonoids. The fruit contains high quantities of vitamin C, B-com-plex vitamins (folates and riboflavin), organic and fatty

Correspondence: V.M. Pavelkić, IHTM, University of Belgrade, Njegoševa 12, 11000 Belgrade, Serbia. E-mail: [email protected] Paper received: 14 October, 2014 Paper revised: 21 January, 2015 Paper accepted: 29 January, 2015

acids, volatiles and minerals such as copper, iron, potassium and magnesium. The chemical compo-sition, the nature and concentrations of pear’s con-stituents are associated with the organoleptic char-acteristics of the pear fruits [1-3]. In addition, pear fruit is one of the very low calorie fruits. Due to these beneficial features, regular consumption of pears is highly recommendable in human nutrition [4].

The common fruit processing techniques are conservation in syrup, juice and drying. Dried fruits are used for many purposes in bakery products, gra-vies and compotes. Ready-to-use intermediate mois-

V.M. PAVELKIĆ et al.: APPLICATION OF PELEG MODEL ON MASS TRANSFER… Chem. Ind. Chem. Eng. Q. 21 (4) 485−492 (2015)

486

ture (IM) food for human consumption has received much attention in recent years. IM products produced by osmotic dehydration (OD) have a higher content of nutrients than those produced by any other drying techniques, because OD has little effect on various internal components. OD of fruits, as a pre-treatment for further steps of drying, presents some benefits such as reducing the damage of heat to the flavor, color, inhibiting the browning of enzymes and dec-rease the energy costs [5,6]. OD is a process of par-tial removal of water by immersing of food (fruit, vege-tables, meat and fish) in different types of solutes such as sucrose, fructose, corn syrup, glucose, salts`, etc., used as osmotic agents for OD [7].

During the OD process the water and small amounts of natural solutes (such as pigments, sugars, organic acids, minerals, vitamins, etc.) diffuse from fruit to the solution and the solute is transferred from the osmotic solution to the fruit tissue in a count-ercurrent mode. It is an efficient form of moisture removal from solid food, causing no change in phase of the water [8]. The weight reduction is approxim-ately 50% of the original weight due to the osmotic dehydration. Mass transfer during osmosis depends on operating parameters such as concentration and type of the osmotic solution, temperature and period of process [9]. According to previous research, tem-perature and concentration of osmotic solution have the highest effect on mass transfer kinetics during the process of osmotic dehydration. In addition, the rate of WL during osmotic dehydration is affected by the immersion time, sample to solution ratio and agitation of the osmotic solution [10-13]. Mass transfer during osmosis occurs through a semi-permeable cell mem-brane and consists of two major simultaneous coun-ter-current fluxes of water and solutes – diffusion of water from food to osmotic solution and diffusion of solute from solution to the food. Leakage of negligible amounts of natural solutes present in the cells into osmotic solution has been considered as third minor flux [14,15].

Mathematical equations describing mass trans-fer during the osmotic drying enable better compre-hension of dehydrated material composition and oper-ating parameters. In this regard, many theoretical and empirical models have been presented in literature, whereas empirical ones have been more popular given their relatively easy application [16-19]. The main goal of existing mathematical models of drying process is prediction of the drying time. The predic-tion of the drying time is the basic data for the sizing and the optimization of an industrial plant drying. Dry-ing rate is always related to one specific product and

one specific operation. In the case of a constant drying rate period, the phenomenon is in steady state. The mathematical models usually based on Fick’s diffusion model for drying studies have been applied to fit drying data of biological materials [20,21].

Peleg model, an empirical one, has been widely used to describe sorption and desorption processes in various foods, i.e., to predict water loss/gain and sugar/salt gain. It has been used to describe water desorption of sago starch, papaya, apricot, cherry tomato, pear, etc. [22-31]. Although it was found that other mathematical model better predict kinetics of the pear osmotic dehydration, according to some authors, Peleg’s equation presents the best fitting for WL and the best adjustment to experimental data. Peleg’s equation parameters have been subjected to analysis of variance and post-hoc Tukey’s HSD test (at 95% confidence limit) to show statistically signi-ficant differences between samples [24,29,32].

With the lack of published experimental data for OD conducted with “Abate Fetel” pears as model fruits, our intention was to obtain additional inform-ation for practical application in OD process design and control. The objective of this work was to exam-ine mass transfer kinetics in terms of WL and SG as a function of concentrations of osmotic solutions, tem-peratures and time of immersion during osmotic treat-ment of pears. Furthermore, the evaluation of appli-cability of Peleg’s equation to experimental data for determination of equilibrium water and solid contents for OD at different concentrations and temperatures as well as the relationship between the Peleg’s spe-cific rate constant and temperature using Arrhenius equation for determination of the activation energy (Ea) for WL and SG were done.

MATERIALS AND METHODS

Preparation of pear samples

Abate Fetel pears were purchased daily from the local market at Belgrade, Serbia. Before experi-ment, fruits were washed and peeled. The peeled pears were manually cut into cubes of 1 cm3, gently blotted with tissue paper to remove the excess of surface moisture and weighed. Initial moisture con-tent, M0, was 84.92±0.99%. Analytical grade sucrose was purchased from Merck. The sucrose solution concentrations were 40, 60 and 70 mass%, and were checked by a digital refractometer (Cole-Parmer, USA). Osmotic treatment were carried out at atmo-spheric pressure, in temperature range from 20 to 50 °C using a circulating water bath (Circulating bath 240 VAC, Cole-Parmer, USA).


487

The pear cubes were immersed in the sucrose solutions, with a sample to solution ratio of 1:10 (w/w). Samples were stirred every 10 min for purpose of easier moving of water that had diffused from the center of the pear cube to its surface and allowing better homogenization of the osmotic solutions. Pro-cessing conditions regarding steering, intensity, dur-ation and frequency of stirring were the same for all concentrations of osmotic solutions, at all tempera-tures, so the results could be comparable. Fruits were removed from the containers after the period of 30, 60, 90, 120, 180, 240, 300 and 360 min, quickly rinsed with distilled water to remove adhered sugar solutions to the surface and gently blotted with tissue paper to remove excess solution from the surface. After each contact time pear cubes were placed in the drying oven (Instrumentaria ST01) at 105 °C for 24 h until constant weight were reached. In order to deter-mine mass change, all samples were weighed before and after treatment using an analytical balance (Met-tler-Toledo, JP 1203C, Switzerland). The solid con-tent of osmotic solutions was determined refractomet-rically (digital refractometer 300034, SPER Scientific Ltd., USA). All analyses were carried out in triplicate and in accordance to AOAC [33].

Kinetic parameters determination

WL and SG of the samples were calculated as follows:

−= 0

0

/ % 100 tM MWLW

(1)

−= 0

0

/ % 100 tS SSGW

(2)

where M0 (g) is the moisture content in fresh fruit; Mt (g) is the moisture content at time t of osmotic treat-ment; S0 (g) is the dry matter of fresh fruit; St (g) is the dry matter after time t of osmotic treatment; W0 (g) is the mass of fresh fruit before the osmotic treatment. Curves of WL and SG as a function of time were constructed using experimental data.

Peleg’s two-parameter equation [15,21,23,24,34] was used for describe sorption kinetics curves that approaches equilibrium asymptotically:

= ±+0

1 2t

tM Mk k t

(3)

where Mt is moisture or solid content (g) at time t (h), M0 is initial moisture or solid content (g), k1 is the Peleg’s rate constant and k2 is the Peleg’s capacity constant. In Eq. (3), “±” becomes “−” for water loss and “+” for solid gain [23].

The first derivative of Eq. (3) gives the rate of sorption (R):

( )= = ±

+1

21 2

ddM kRt k k t

(4)

The Peleg’s rate constant k1 relates to dehyd-ration rate at the beginning, t = t0, and is inversely proportional to initial rate of dehydration [24]:

= ±1

d 1dMt k

(5)

The Peleg’s capacity constant k2 relates to minimum attainable moisture content, so at time t→∞ Eq. (4) gives the relation between equilibrium mois-ture content (Meq) and k2 [23,31]:

= ±eq 02

1M Mk

(6)

Rearrangement and linearization of Eq. (4) give the possibility for graphical determination of the Peleg’s kinetics parameters [24]:

= ±− 1 2

0

t k k tM M

(7)

The plot of Eq. (7) is a straight line, where k1 is the intercept and k2 is the slope [23].

The quantification of the drying can be made by the quantification of the energy received by the mat-erial that is being dried. This energy is equal to the energy necessary for the vaporization of the water removed during the drying. In the decreasing drying rate period, namely the unsteady state, the behavior of the material during the drying is due to the domin-ation of internal resistance. The distinctions of these drying periods are obtained by drying rates calcul-ations from drying curves. In order to find the effect of temperature on water desorption of pears, an Arrhe-nius type equation was used for modeling the depen-dence of Peleg’s rate constant (k1) on temperature [28].

The linearized Arrhenius equation represents the temperature dependency of the Peleg’s rate cons-tant:

= − a1 0ln ln

Ek kRT

(8)

where k1 is the Peleg’s rate constant for WL or SG (h (g/g dm)-1); k0 is a constant (h(g/g dm)-1); Ea is the activation energy (kJ/mol), R is the universal gas con-stant (8.314 J mol-1 K-1) and T is absolute temperature in K.


488

The criterion used to evaluate the best fitting model was their average relative error, E:

=

−=

eexp p

e exp1

1n

i

X XE

n X (9)

where ne is the number of experimental data, Xexp is the experimental value for WL or SG, and Xp is the calculated value for WL or SG.

Statistical analysis

Descriptive statistical analyses for Peleg’s equa-tion parameters were expressed as the mean ± standard deviation (SD). Post-hoc Tukey’s HSD tests at 95% confidence limit have been calculated to show significant differences between observed samples. These calculations and the residual analysis were performed using StatSoft Statistica 10 software (Stat-soft Inc., Tulsa, OK, USA).


The experiments of osmotic dehydration of pears were carried out at three different concentra-tions and three different temperatures. Figures 1 and 2 show the experimental data for WL and SG as a function of time of osmotic treatment of pear at differ-ent concentrations of sucrose solution, at 35 °C (data obtained of experiments conducted at 20 and 50 °C not shown). Three-dimensional graphics have been plotted for regression model (surface plot) compar-ison, with experimental data visualization (white col-ored points). As can be seen, WL and SG increased non-linearly with immersion time at all concentrations

and temperatures. From the observed data presented in Figures 1 and 2, the trend of the faster mass trans-fer rate in the initial period of osmotic treatment is clear, and is followed by slower removal of water and uptake of sugar from fruit tissue in later stages. This reduction of the mass transfer rate might be result of the formation of the solid layers at the surface of the fruit tissue, which hinders transfer of water and solids [35]. The WL and SG increase with increasing suc-rose concentration at constant temperature, as well as with increasing temperature of the osmotic sol-ution. An initial increase of WL and SG probably occurred because of the osmotic driving force differ-ence between the dilute juice of the pear cubes and the surrounding hypertonic sucrose solution. The inc-rease of WL and SG with the higher solution concen-tration is due the high concentration difference between the pear and osmotic solution that increased the rate of diffusion of solute and water exchange with osmotic solution [28,35,36]. Higher temperatures of osmotic solution additionally cause increase in kin-etics of mass transfer. Higher temperatures seem to promote faster water loss through swelling and plas-ticizing of cell membranes as well as the better water transfer characteristics on the product surface due to lower viscosity of the osmotic medium [29,37,38]. This enhanced removal of water and uptake of solids showed that immersion time and concentration of sucrose solution were significant factors affecting WL during osmotic dehydration of followed by tempera-ture [30].

> 6 < 6 < 4 < 2

70

60

50

40 0

100200

300

10

8

6

4

2

SG (%)Temperature=35 Co

Time (min)Concentration (%)

SG (%)2

4

6

Figure 2. Experimental and calculated values of SG during osmotic dehydration of pears cubes at 35 °C and sucrose

solutions with concentrations: 40, 60 and 70 mass%.

After 360 min of osmotic treatment of pears, WL ranges from 23.71 to 31.68% at 20 °C, from 24.80 to

> 30 < 30 < 20 < 10

50

40

30

20

10

70

60

50

40 0

100200

300

Time (min)Concentration (%)

WL (%)Temperature=35 Co

WL (%)10

20

30

Figure 1. Experimental and calculated values of WL during osmotic dehydration of pears cubes at 35 °C and sucrose

solutions with concentrations: 40, 60 and 70 mass%.


489

40.38% at 35 °C and from 33.30 to 52.07% at 50 °C, of initial weight of pears (Figure 1). The increase of the dry mass of the samples, SG, after 360 min of osmotic treatment ranges from 3.02 to 6.68% at 20 °C, from 4.15 to 7.71% at 35 °C and from 5.00 to 8.92% at 50 °C (Figure 2).

The WL/SG ratio is influenced by temperature and concentration of the sucrose solutions, as well as with the duration of the osmotic treatment. Higher values of WL/SG ratio implies the intensive water removal from the samples followed by minimal SG. After initial increase of the WL/SG ratio during OD treatment of pear at first 30 min of process, WL/SG ratio decreased, depending of experimental condi-tions. The minimal ratio of 4.47 was obtained at 35 °C, 60% sucrose solutions and after 120 min of OD treatment duration. The maximal value of 7.85 was obtained at 50 °C, 40% sucrose solution and after 30 min of OD treatment.

Peleg’s equation and equilibrium values for WL and SG at different experimental temperatures were used to calculate Peleg’s rate constant, k1 and capacity constant k2 for both processes. Peleg’s equation parameters for WL and SG are shown in Table 1. Peleg’s rate constants k1

WL and k1SG

decreased from 1.12 to 0.51 h (g/g dm)-1 and from 5.48 to 2.17 h (g/g dm)-1 at 20 °C with increasing concentration of osmotic solution from 40 to 70 mass%, respectively. Rate constant k1

WL decreased from 0.58 to 0.41 h (g/g dm)-1 and from 0.33 to 0.28 h (g/g dm)-1 at 35 and 50 °C, respectively. In addition, rate constant k1

SG decreased from 4.33 to 1.58 h (g/g dm)-1 and from 0.33 to 0.28 (g/g dm)-1 at 35 and 50 °C, respectively. The concentration of osmotic sol-utions, at each experimental temperature, increased from 40 to 70 mass%. Since the reciprocal value of k1

describes the initial mass transfer rate through the osmotic treatment, observed results indicate an inc-rease of the initial mass transfer rate with increasing the concentration and temperature of osmotic solution [35]. The capacity constant, k2 is associated with equilibrium moisture content and equilibrium solid content, e.g., the lower the k2, the higher the equilib-rium moisture content [10,31,35]. Both capacity con-stants k2

WL and k2SG, also exhibit the same trend, i.e.,

the inverse relationship between capacity constant and temperature, as well as concentration of the osmotic solution. The statistical parameter (R2) ranged from 0.936 to 0.997 for WL and SG, respectively.

The equilibrium point is reached when water activities of osmotic solutions and dehydrated fruit product become equal. The experimental equilibrium point were reached after 360 min of the osmotic treatment in some of the samples (Table 2), while in the others experimentally obtained values were very close to the ones calculated by Peleg’s model. According to this, it would be reasonable to claim that 360 min is a long enough period to reach equilibrium. Since both WL and SG influence decrease in water activity, their relationship is important for the attain-ment of the equilibrium [10,31,35]. The predicted and experimental equilibrium values for moisture content and SG at different experimental temperatures and concentrations of osmotic solutions are shown in Table 2. As can be seen, slight differences between the equilibrium experimental data and predicted values by the Peleg’s model were observed (Table 2). Table 2 also shows the residual analysis, which is performed to check the assumptions of indepen-dence, normality, homoscedasticity and zero mean of errors. The mean of residuals are close to zero, and the standard deviation of Meq and Seq were 0.11 and

Table 1. Peleg’s equation parameters and goodness of fit for SG and WL during osmotic treatment of pear; a-dvalues with the same letter within a column are not statistically different at the p < 0.05 level (according to post-hoc Tukey’s HSD test)

t / oC Conc., % Water loss Solid gain

k1WL / h (g/g dm)-1 k2

WL / h (g/g dm)-1 R2 k1SG / h (g/g dm)-1 k2

SG / h (g/g dm)-1 R2

20 40 1.12±0.23a 0.52±0.07cd 0.962 5.48±2.87a 5.50±0.84a 0.936

60 0.64±0.10b 0.51±0.03c 0.991 2.89±0.47cd 3.42±0.25c 0.984

70 0.51±0.12c 0.48±0.03d 0.984 3.20±0.51c 2.17±0.15f 0.986 0.936

35 40 0.58±0.13bc 0.62±0.04a 0.989 4.33±0.58b 3.54±0.17b 0.993

60 0.45±0.09cd 0.45±0.03d 0.990 2.46±0.86cd 1.67±0.14h 0.980

70 0.41±0.05cd

0.58±0.13 0.34±0.02a 0.993 1.58±0.35cd 2.75±0.11d 0.995

50 40 0.33±0.08d 0.54±0.02c 0.994 1.70±0.47cd 3.65±0.14b 0.996

60 0.15±0.05e 0.49±0.02d 0.997 1.12±0.36d 2.52±0.10e 0.995

70 0.28±0.07d 0.32±0.02e 0.987 0.994

0.97±0.37d 1.85±0.10g 0.991


490

0.05, respectively. These results showed a good approximation to a normal distribution around zero with a probability of 95% (2×SD), which means a good generalization ability of developed models for the range of observed experimental values (the skew-ness parameter showed minimal deviations from nor-mal distribution, while the Kurtoisis parameter showed almost neglecting difference in "peakedness" com-pared to normal distribution).

The comparison between experimental and Peleg-predicted values for moisture content and SG during osmotic dehydration treatment of pears at 20, 35 and 50 °C in 40% sucrose solution are shown in Figures 3 and 4. It is observed that the differences between the data and the predicted ones were small. The parameters, statistical R2, as well as the relative error, E (%), were used for characterizing the fitting to the Peleg’s model. As statistical parameter, R2, ranges from 0.936 to 0.997 for moisture content and SG, and E (%) value is below 10%, the Peleg model can be account as acceptable for the description of the WL and SG kinetic in the osmotic dehydration of pears cubes.

The influence of temperature on WL and SG kinetics were checked out by applying the Arrhenius type equation for modeling the Peleg’s rate constant dependence on temperature. According to Eq. (8), the plot of the ln k1 (natural logarithm of Peleg’s rate con-stant) versus reciprocal of temperature, 1/T, resulted in a straight line with the slope equal Ea/R and inter-cept equal ln k0. The graphically obtained parameters of Arrhenius equation for the Peleg’s rate constant of SG and WL at different sucrose concentrations are presented in Table 3 (figures not shown).

3.0 3.5 4.0 4.5 5.0Mtcalculated (g/gdm)

Mt e

xper

imen

tal (

g/gd

m)

3.0

4.0

5.0

4.5

3.5

50 Co

35 Co20 Co

Concentration=60%

Figure 3. Comparison between experimental and calculated

values of moisture content of pears cubes during osmotic dehydration treatment in sucrose solution with concentrations

60% and at 20, 35 and 50 °C.

S g calculated (g/gdm)

Sg e

xper

imen

tal (

g/gd

m) 50 Co

35 Co20 Co

Concentration=60%

0.85 0.90 0.95 1.00 1.05 1.10

0.85

0.90

0.95

1.00

1.05

1.10

Figure 4. Comparison between experimental and calculated

values of solid gain of pears cubes during osmotic dehydration treatment in sucrose solution with concentrations 60% and at

20, 35 and 50 °C.

Table 2. Experimental and Peleg predicted values for equilibrium values for WL and SG during osmotic dehydration treatment

t / oC Conc., % Water loss Solid gain

Meqexperimental / g/(g dm) Meq

Peleg / g/(g dm) Residual Seqexpperimental / g/(g dm) Seq

Peleg / g/(g dm) Residual

20 40 3.845 3.877 0.032 1.068 1.087 0.019

60 2.987 3.039 0.052 1.195 1.205 0.01

70 3.627 3.516 -0.111 1.331 1.366 0.035

35 40 3.539 3.507 -0.032 0.968 1.019 0.051

60 4.637 4.733 0.096 1.404 1.443 0.039

70 2.077 1.984 -0.093 1.253 1.238 -0.015

50 40 2.732 2.649 -0.083 1.115 1.073 -0.042

60 2.403 2.648 0.245 1.276 1.191 -0.085

70 1.096 1.036 -0.06 1.236 1.279 0.043

Residual analysis

Mean Min. Max. Variance Std. dev. Std. err. Skewness Kurtosis

Meq 0.01 -0.11 0.25 0.01 0.11 0.04 1.19 1.22

Seq 0.01 -0.09 0.05 0.00 0.05 0.02 -1.15 0.59


491

Table 3. Parameters of Arrhenius equation for the Peleg rate constant of SG and WL at different sucrose concentrations

Parameter Concentration, %

70 60 40

Water loss

ln k0 1.12±0.13 -7.61±0.84 -4.87±0.20

Ea / kJ mol–1 15.65±2.91 37.73±1.37 32.09±0.52

R2 0.98 0.95 0.99

Solid gain

ln k0 -3.55±0.94 -0.74±0.08 -2.46±0.48

Ea / kJ mol–1 31.40±2.41 24.59±1.17 30.40±1.44

R2 0.99 0.92 0.94

Energy required to initiate water removal and solid uptake, when pear cubes were immersed in 40, 60 and 70% osmotic solutions at 20, 35 and 50 °C were determined using Eq. (8). Activation energy for WL and SG varied from 15.65 to 32.09 kJ/mol and 31.40 to 30.40 kJ/mol, respectively. The lowest acti-vation energy value was found for samples immersed into a 70% sucrose solution. This confirms the report that osmotic dehydration has low energy requirement [34], especially when carried out at higher concen-tration. The linearity of the data (R2 > 0.92) reveals that the k1 for all the kinetics terms followed an Arrhe-nius relationship as a function of temperature for each applied sucrose concentration. Higher values of Ea revealed the greater temperature sensitivity of rate constant k1 [35]. Depending on sucrose concentra-tion, it was found that the rate constant for WL is more temperature sensitive than the rate constant for SG (Table 3.) for 40 and 60 mass% sucrose concentra-tion. At higher sucrose concentration (70 mass%) the rate constant for SG is more temperature sensitive compared with the rate constant for WL.

CONCLUSION

The influence of concentration and temperature on mass transfer kinetics was investigated through WL and SG during osmotic dehydration treatment of pear cubes. The SG and WL increased with inc-reasing sucrose solution concentration and tempera-ture during osmotic treatment of pear. Peleg model was successfully applied to the experimental data and for description of the osmotic dehydration process. From the experimental data, equilibrium values for moisture and solid content were estimated using Peleg’s equation. The model predicted equilibrium values fitted very good to experimental ones, which is confirmed with high coefficients of determination and by the residual analysis. The Arrhenius equation was successfully applied to evaluate the temperature

dependency of the Peleg’s rate constant and acti-vation energy determination.

Nomenclature

IM - Intermediate moisture OD - Osmotic dehydration WL - Water loss SG - Solid gain Ea - Activation energy (kJ/mol) M - Moisture content (g) k1 - Peleg’s rate constant (h (g/g dm)-1) k2 - Peleg’s capacity constant (h (g/g dm)-1) dm – dry matter R - universal gas constant (8.314 J/g mol K) R2 - coefficient of determination T - temperature (K) t - time (s) E - average relative error (%) ne - number of experimental data

Subscripts eq - equilibrium 0 - initial

Acknowledgement

This study was financial supported by Ministry of Education, Science and Technological Development of the Republic of Serbia, project No. TR 31055.

REFERENCES

[1] J. Chen, Z. Wang, J. Wu, Q. Wang, X. Hu, Food Chem. 104 (2007) 268–275

[2] M. Colaric, F. Stampar, A. Solar, M. Hudina, J. Sci. Food Agric. 86 (2006) 2463–2467

[3] A.C. Galvis-Sanchez, A. Gil-Izquierdo, M.I. Gil, J. Sci. Food Agric. 83 (2003) 995–1003

[4] D. Komes, A. Belščak-Cvitanović, Z. Domitran, M. Opalić, J. Food Nutr. Res. 52 (2013) 239-250

[5] J.S. Alakali, C.C. Ariahu, N.N. Nkpa, J. Food Process. Preserv. 30 (2006) 597-607

[6] J.D. Torres, P. Talens, I.A. Escriche, J. Food Eng. 74 (2006) 240-246

[7] E. Azuar, I. Cesar, I. Beristain, G.F. Gutierrez, J. Food Process. Preserv. 26 (2002) 295–306

[8] H.R. Bolin, C.C. Huxsoll, R. Jackson, J. Food Sci. 48 (1983) 202–205

[9] C.R Lerci, G. Pinnavaia, M.D. Rosa, L. Bartolucci, J. Food Sci. 50 (1988) 12-17

[10] N.M. Mišljenović, G.B. Koprivica, L.L. Pezo, T.A. Kuljanin, M.I.B. Solarov, B.V. Filipcev, Acta Period. Technol. 42 (2011) 91-100

[11] J. Conway, F. Castaigne, G. Picard, X. Vevan, Can. Inst. Food Sci. Technol. J. 16 (1983) 25-29

[12] N.K. Rastogi, K.S.M.S. Raghavarao, J. Food Eng. 34 (1997) 429-440


492

[13] A.L. Raoult-Wack, Trends in Food Sci. Technol. 5 (1994) 255–260

[14] M.N. Islam, J.M. Flink, J. Food Technol. 17 (1982) 387- -392

[15] P.S. Madmba, Draying Technol. 21 (2003) 1759-1780

[16] N.M. Mišljenović, G.B. Koprivica, L.L. Pezo, Lj.B. Lević, B.Lj. Ćurčić, V.S. Filipović, M.R. Nićetin, Тher. Sci. 16 (2012) 43-52

[17] G.B. Koprivica, L.L. Pezo, B.Lj. Ćurčić, Lj.B. Lević, D.Z. Šuput, J. Food Process. Preserv. 38 (2014) 1705-1715

[18] V. Filipović, Lj. Lević, B. Ćurčić, M. Nićetin, L. Pezo, N. Mišljenović, Chem. Ind. Chem. Eng. Q. 20 (2014) 305– –314

[19] A. Matusek, B. Czukor, P. Meresz, F. Orsi, Hung. J. Ind. Chem. 33 (2005) 43-48

[20] V.T. Karathanos, G. Villalobos, G.D. Saravacos, J. Food Sci. 55 (1990) 218–223

[21] J.D. Daudin, Sci. Aliments 3 (1983) 1–36

[22] N.K. Rastogi, K.S.M.S. Raghavarao, Trends Food Sci. Technol. 37 (2004) 43-47

[23] M. Turhan, S. Syar, S. Gunasekaran, J. Food Eng. 53 (2002) 153-159

[24] P.M. Azoubel, F. Murr, J. Food Eng. 61 (2004) 291-295

[25] H.N. Lazarides, V. Gekas, N. Mavroudis, J. Food Eng. 31 (1997) 315–324

[26] J.E. Contreras, T.G. Smyral, Can. Inst. Food Sci. Technol. J. 14 (1981) 310–314

[27] B.M. Uddin, P. Ainsworth, S. Ibanoglu, J. Food Eng. 65 (2004) 473–477

[28] R.M. Khoyi, J. Hesari, J. Food Eng. 78 (2007) 1355-1360

[29] K.J. Park, A. Bin, F.P.R. Brod, T.H.K.B. Park, J. Food Eng. 52 (2002) 293–298

[30] M. Peleg, J. Food Sci. 53 (1988) 1216–1217

[31] O. Corzo, N. Bracho, J. Food Eng. 75 (2006) 535-541

[32] A. Ganjloo, R.A. Rahman, J. Bakar, A. Osman, M. Bimakr, Int. Food Res. J. 18 (2011) 1105-1110

[33] K. Heigich, J. AOAC Int. 15 (1990) 912

[34] N.M. Panagiotou, V.T. Karathanos, Z.B. Maroulis, Drying Technol. 17 (1999) 175–189

[35] A, Ganjloo, R.A. Rahman, J. Bakar, A. Osman, M. Bimakr, Food Bioprocess Technol. 5 (2012) 2151-2159

[36] K.O. Falade, J.C. Igbeka, F.A. Ayanwuyi, J. Food Eng. 80 (2007) 979-985

[37] B. Singh, A. Kumar, A. K. Gupta, J. Food Eng. 79 (2007) 471–480

[38] B.M. Uddin, P. Ainsworth, S. Ibanoglu, J. Food Eng. 65 (2004) 473–477.

ВЕСНА М. ПАВЕЛКИЋ1

ТАЊА П. БРДАРИЋ2

МАРИЈА П. ПЕТРОВИЋ3

ГАВРИЛО М. ШЕКУЛАРАЦ1

МИЛИЦА Г. КОШЕВИЋ1

ЛАТО Л. ПЕЗО4

МАРИЈА А. ИЛИЋ5 1Научна установа ИХТМ,

Универзитет у Београду, Београд, Србија

2Институт за нуклеарне неуке Винча, Универзитет у Београду, Београд,

Србија 3Институт „Кирило Савић“ а.д.,

Београд, Србија 4Институт за општу и физичку

хемију, Београд, Србија 5Рударско-геолошки факултет,

Универзитет у Београду, Београд, Србија

НАУЧНИ РАД

ПРИМЕНА ПЕЛЕГОВОГ МОДЕЛА НА КИНЕТИКУ ТРАНСФЕРА МАСЕ ТОКОМ ОСМОТСКЕ ДЕХИРАТАЦИЈЕ КРУШКЕ У РАСТВОРУ САХАРОЗЕ

У раду је испитивана применљивост Пелеговог модела за предикцију кинетике трансфера масе током процеса осмотске дихдратације крушака, на различитим концентрацијама (40, 60 и 70 мас.%) и темпертурама (20, 35 и 50 °C) раствора саха-розе. Повећање концентрације раствора сахарозе доводи до већег губитка воде (ГВ) и повећања суве материје (СМ) током процеса осмотске дехидратације. После 360 min осмотског третмана крушака, ГВ се креће од 23,71 до 31,68% на 20 °C, од 24,80 дo 40,38% на 35 °C и од 33,30 дo 52,07% на 50 °C од почетне масе крушака. Повећање суве материје у узорцима, СМ, после 360 min осмотског третмана креће се од 3,02 до 6,68% на 20 °C, од 4,15 дo 7,71% на 35 °C и од 5,00 дo 8,92% на 50 °C. Пелегове константе брзине, k1

ГВ и k1СМ, опадају са повећањем температуре, а такође

опадају са повећањем концентрације осмотског раствора на константној темпера-тури. Обе капацитивне константе, k2

ГВ и k2СМ, такође показују инверзно понашање у

односу на температуру и концентрацију осмотског раствора. Пелегове константе брзине процеса ГВ и СМ на свим температурама прате функционалну зависност Аренијусовог типа. Моделом предвиђене равнотежне вредности су блиске експери-менталним, што је потврђено високим коефицијентима одређивања и резидуалном анализом.

Кључне речи: oсмотска дехидратација, крушке, кинетика, ефекат темпера-туре, Пелегов модел.




493

RONGYAN SHEN FANG LIU

TE LI XIA XU

YUTING LIANG XINGQING ZHAO

WENYI ZHANG

School of Environmental and Safety Engineering, Changzhou

University, Wujin District, Chang-zhou City, Jiangsu Province, China

SCIENTIFIC PAPER

UDC 628.3:544.526.5:66

DOI 10.2298/CICEQ140609005S

TREATMENT OF 2-DIAZO-4,6-DINITRO-PHENOL WASTEWATER USING TIO2/SIO2 COMPOSITE FILM IN A PHOTOCATALYTIC REACTOR

Article Highlights • Photocatalytic activity of filter media modified by TiO2/SiO2 was evaluated using DDNP

wastewater • By modified filter media, removal rates of chroma and COD separately reached 70.00

and 60.85% • Optimal working parameters were: 59:1 of Ti/Si, pH 1, 7 ml L-1 H2O2, and 3000 times

chroma • Under optimal condition, decolorization and COD removal rate separately reached

98.50 and 92.50% Abstract

TiO2/SiO2 composite film was used to modify the surface of the filter media sintered by coal refuse. 2-Diazo-4,6-dinitrophenol (DDNP) wastewater was used as the response substrate to test its photocatalytic activity in the self-made photocatalytic reactor. The influencing factors of the photocatalytic acti-vity of the modified filter media were studied. When the modified filter media was used, the decolorization rate and COD removal rate of DDNP wastewater reached 70.00 and 60.85%, respectively. But unmodified filter media almost had no photocatalytic activity. The orthogonal test showed that the optimal working parameters separately were: 59:1 of Ti/Si in the TiO2/SiO2 composite film, pH 1, 7 ml L-1 H2O2 and 3000 times chroma (equivalent initial concentra-tion of DDNP wastewater). Under the above condition, the decolorization rate and COD removal rate separately reached 98.50 and 92.50% after 1 h photo-catalytic reaction. They were far higher than those in the reaction catalyzed by pure TiO2. Furthermore, under the condition of illumination and aeration, the photocatalytic activities were obviously higher than those under only illumin-ation or aeration.

Keywords: TiO2/SiO2, photocatalysis, modification, DDNP, decolorization rate, COD.

2-Diazo-4,6-dinitrophenol (DDNP) has been widely used as an important and effective explosive [1]. It is an energetic compound and a very promising initiator [1-4]. But in the producing process of DDNP, the accompanying DDNP wastewater contained many toxic substances such as two nitro diazo phenol, nitro

Correspondence: W. Zhang, School of Environmental and Safety Engineering, Changzhou University, No 1 Gehu Road, Wujin District, Changzhou City, Jiangsu Province, 213164, China. E-mail: [email protected]; [email protected] Paper received: 9 June, 2014 Paper revised: 28 November, 2014 Paper accepted: 4 February, 2015

compounds, sulfide, phenol, etc. DDNP wastewater had the characteristics of higher chroma, higher COD, higher toxicity, and complicated composition, etc. [5,6]. If untreated DDNP wastewater was discharged into river, it would severely pollute the environment and threaten the health of people [7]. This problem has attracted the researchers’ extensive attention.

At present, the main methods of treating DDNP wastewater are adsorption method, microelectro-lysis/H2O2 method, and biochemistry method [7,8]. But the cost of these methods was high. And some methods are in the period of exploration, and it is dif-ficult for them to be applied and promoted [9,10]. Pho-tocatalytic oxidation was a newly developed techno-

R. SHEN et al.: TREATMENT OF 2-DIAZO-4,6-DINITROPHENOL WASTEWATER… Chem. Ind. Chem. Eng. Q. 21 (4) 493−499 (2015)

494

logy. Sunlight was used as a potential radiation source. It could stimulate the generation of the hole-electron pairs. So strong redox occurred in this method. Many pollutants could be treated by this method.

Coal gangue is the largest solid waste in our country. Its emission and accumulation not only take up a large number of cultivated land, but also cause great pollution and endanger people’s health. It has become a public nuisance. The comprehensive deve-lopment and utilization of coal gangue are urgent and imperative in our country. As the main component of sintered filter material, coal gangue would not only satisfy the basic requirement of water treatment, but also have obvious mineralogy characteristics of crys-tal. It was widely used in wastewater treatment because of its many surface pores, large roughness, and more stable performance. Coal gangue and its sintered products often contain a lot of quartz and scale quartz. So their surface and photocatalytic acti-vity can be increased by nano modification.

As a kind of typical nanomaterials, titanium diox-ide (TiO2) was widely used in pollutants processing due to its non-toxicity, high-stability, and photo-elec-tric properties [11-16]. Despite many good properties, there were certain problems associated with nano-metric TiO2. Such problems included nanoparticles agglomeration [17], phase transformation [18,19], decrease in surface area upon thermal treatment [19,20], recombination of photogenerated electron- –hole pair [21], lack of visible light photo activity due to its wide band gap (Eg = 3.2 eV), etc. [21]. Furthermore, the photocatalytic efficiency of pure TiO2 in photocat-alytic reactions was found to be limited in our pre-vious study [16]. To solve most of these problems, many TiO2-based composite photocatalysis have been prepared to enhance the photocatalytic activity [11,12]. In comparison to those single-phase titania materials, these composites tend to show higher photoactivity [22-24]. These composites were usually composed of titania and other functional metals/metal oxides nanoparticles such as SiO2, ZrO2, MoO3 and Fe2O3 [25,26]. Silica was one of the best core mat-erials [27,28] due to its rich and well-known surface chemistry and adsorption capacity [29].

To efficiently and economically treat the DDNP wastewater of higher chroma and further improve the photocatalytic activity of the sintered filter media, the glass photocatalytic reactor [16] was used and the TiO2/SiO2 composite film was prepared. And the influ-encing factors of photocatalytic activity of TiO2/SiO2 composite film were investigated.

EXPERIMENTAL

Preparation of the filter media modified by TiO2/SiO2

Firstly, the modified filter media was prepared by the liquid phase deposition method [16]. (NH4)2TiF6, (NH4)2SiF6 and H3BO3 were used as the precursors. The mole ratio of (NH4)2TiF6 + (NH4)2SiF6 and H3BO3 was 1:3. The molarity of (NH4)2TiF6 was 0.1 mol L-1 and the used concentrations of H3BO3 were 0.2, 0.3, and 0.4 mol L-1. The distilled water was used as the solvent of the coating solution. The other steps were same as the reference [16]. After certain time, the sin-tered filter media modified by the TiO2/SiO2 composite film was obtained.

Characterization of the modified filter media

Particle morphology and physico-chemical pro-perties of the filter media modified by TiO2/SiO2 were characterized by the same methods in the reference [16]. The background of surface of the modified filter media was bright. This was due to the reflection because of the presence of TiO2 thin film. And light was reflected on uneven surface many times. This would inevitably increase the absorption and util-ization of light. It would be advantageous to the catal-ytic reaction. Although the surface of the unmodified filter media was very rough and there were many irregular holes, its particle surface was smoother. There were a large number of small bumps and uni-form distribution on the particle surface of the modi-fied filter media. They were TiO2 grains (30-50 nm). These particles pilinged up in together in different ways. This made the micro-structure of the surface of modified filter media change. The specific surface area of the modified filter media was greatly imp-roved. It was advantageous to the adsorption of more ultraviolet light. In our previous study we found that the main components of the unmodified filter media were silicon, aluminum, oxygen, carbon, calcium, and iron. Titanium elements existed in the energy spec-trum diagram of modified filter media. And they existed in the form of TiO2 compounds. The weight percentage and atomic percentage of titanium were 0.99 and 0.40%, respectively. There were a large number of alpha-quartz crystal, scale quartz and cal-cium feldspar in the mineral phase structure. TiO2 crystal could not be found in unmodified filter media. But new TiO2 crystal was found in XRD atlas of modi-fied filter media. The superposition phenomenon existed in the diffraction peaks of TiO2 crystals and calcium feldspar crystal.


495

Photocatalytic reactor

The photocatalytic reactor was same as the one used in our previous work [16]. The interlayer was the photocatalytic reaction unit filled with the sintered filter media modified by the TiO2/SiO2 composite film. The reactor had already been described in details elsewhere [16].

Orthogonal test design

The orthogonal test design is a method that util-izes an orthogonal test table to organize the tests and to scientifically analyze the test results before deci-sion-making. This paper firstly analyzed the main parameters that affected the photocatalytic activity of TiO2/SiO2 composite film and their respective levels and then discussed the conducted orthogonal test to optimize the parameters of the photocatalytic system.

Based on the effects of varied factors on DDNP wastewater degradation, the mole ratio of Si and Ti in the TiO2/SiO2 composite film, chroma (initial concen-tration), pH and addition amount of H2O2 were sel-ected as the orthogonal test factors. Each factor was taken three levels. There were 27 combinations to be tested in the orthogonal test L9 (34). We applied the orthogonal array to select nine representative combi-nations to be tested. The factors and levels were shown in Table 1.

Table 1. Factors and levels of orthogonal test

Level Factor

Mole ratio of Ti and Si (A)

Initial chroma (B)

pH (C)

H2O2 addition amount, ml L-1 (D)

1 39:1 5000 1 7

2 59:1 3250 3 9

3 79:1 3000 5 11

Analysis method

In the process, COD removal rate and decol-orization rate were evaluated. The COD values were determined by the potassium dichromate method. The variation of absorbency was characteristic of the decolorization efficiency. The variation of absorbency was calculated by the formula [16].


Influencing factors of the photocatalytic activity of the modified filter media

Under the condition of neutral and room tempe-rature, the photocatalytic degradation experiment of DDNP wastewater with 5000 times chroma (initial concentration) was conducted. The decolorization

rate and COD removal rate of unmodified filter media reached 18.00 and 22.64%, respectively. But after the filter media was modified by the TiO2/SiO2 composite film, the decolorization rate and COD removal rate reached 70.00 and 60.85%, respectively. They were far higher than those in the reaction catalyzed by pure TiO2 [16]. This indicated that the modified filter media had better photocatalytic degradation activity.

Then, a series of photocatalytic reactions were conducted to further improve the photocatalytic acti-vity of the modified filter media. DDNP wastewater of 3250 times chroma and 317.99 mg L-1 COD was treated and different influencing factors were analyzed.

Influence of mole ratio of Ti and Si

The experiments without irradiation had been done in previous study reported in the China Water and Wastewater. The decolorization rates were all very small (< 7%) [30]. In present study, the decol-orization rates of 24 h were also very small (< 2%) and the results had no significant difference. So the adsorption of the composite films of different Ti/Si was neglected in further study.

In present study, when the mole ratio of Ti and Si in the TiO2/SiO2 composite film was 59:1, the pho-tocatalytic activity of the modified filter media was best (Figure 1). The decolorization rate and COD removal rate were 70.00 and 60.85%, respectively.

0

10

20

30

40

50

60

70

80

19:1 39:1 59:1 79:1 99:1

Mole ratio of Ti and Si

Rem

oval

rate

(%)

COD removal rateDecolorization rate

Figure 1. Effect of mole ratio of Ti and Si on removal rate.

In TiO2/SiO2 composite film, the Si-O-Ti bond formed between SiO2 and TiO2, and then SiO2 with net structure entered into the compound [31]. SiO2 net inhibited the TiO2 mass transport and reduced the growth rate of crystal particle. So the TiO2 particle size in TiO2/SiO2 compound with uniform composition could be well controlled. The reduction of particle size increased the width of the forbidden band, and the effect of quantum size was significant. This caused the energy increase of band gap. The time that carrier


496

was diffused from interior to surface of catalyst short-ened in photocatalytic reaction, and the separation efficiency of photo-generated electron and hole was improved. So the photocatalytic degradation activity was enhanced. However, SiO2 did not have photo-catalytic activity. So, when TiO2 surface was occupied by more SiO2, its effective surface reduced. Under the condition, it was not easy for the photo-generated electron and the hole to produce [32]. Hence, if the content of SiO2 in the TiO2/SiO2 composite film was too high, the photocatalytic activity of composite film would decline.

Influence of chroma

When the chroma of DDNP wastewater was 3250 times, the decolorization rate and COD removal rate reached the highest value (Figure 2). The higher the initial concentration of solution was, the weaker the penetrating ability of ray was, and the lower the amount of photons which participated in photocat-alytic reaction was. More solute was adsorbed on the surface of catalyst, and the active site reduced [31]. These inhibited the catalyst to absorb the ultraviolet and produce the •OH. So the photocatalytic efficiency reduced. Though the decolorization rate was high when the initial concentration was too low, the amount of treated DDNP wastewater was low. The degradation ability of photocatalytic reaction could not be fully exerted. In the experiment, the surface ads-orption of the TiO2/SiO2 composite film reached satur-ation because of overhigh concentration wastewater. Most active sites of the TiO2/SiO2 composite film sur-face were occupied due to surplus organic molecular. And the absorption of ultraviolet and the production of •OH were influenced. But the photocatalyst could not be fully applied because of overlow concentration wastewater, which affected the degradation efficiency.

0

10

20

30

40

50

60

70

80

7500 5000 3250 3000 2500

Chroma (time)

Rem

oval

rate

(%)


Figure 2. Effect of chroma on removal rate.

Influence of reaction time

When the reaction time was more than 60 min, the efficiencies of photocatalytic degradation tend to be steady (Figure 3). And the decolorization rate and COD removal rates were 73.85 and 65.17%, respect-ively. The oxidation reaction incompletely happened when illumination time was too short, so the removal was not good. Too long illumination time had no sig-nificant effect on the removal of pollutant.

0102030405060708090

15 30 45 60 75 90Time (min)

Rem

oval

rate

(%)


Figure 3. Effect of reaction time on removal rate.

Influence of pH

Under the acidic condition, the decolorization rate and COD removal rate both reached the maxi-mum which were 81.54 and 72.34%, respectively (Figure 4). When pH was more than 7, the decolor-ization rates declined with the rising of pH. The vari-ation of pH would impel the change of electrification state of TiO2 surface. When pH was below 3.5, the particle surface took positive charge. And it was beneficial for the photo electron to migrate to the surface of catalyst. And the electron reacted with O2 adsorbed by catalyst, so the combination of E- and H+ was inhibited. Furthermore, pH of solution directly affected the surface state, interfacial potential, sur-face charge, and aggregation of TiO2 [33]. The iso-electric point of TiO2 was about 6.5. When pH was more than 6.5, the surface charge was negative and the main form was TiO-. And when pH was below 6.5, the surface charge was positive and the main form was TiOH2

+. The characteristic of surface charge affected the TiO2 surface adsorption of organic mole-cules, and affected the migration of photo electron and hole from the interior to the surface of TiO2 [31- –33]. Due to different surface morphology and surface charge, the adsorption ability of catalyst was signific-antly different, so the process of photodegradation was affected.


497

0102030405060708090

15 30 45 60 75 90Time (min)

Rem

oval

rate

(%)


Figure 4. Effect of pH on removal rate.

Influence of H2O2 addition amount

The optimal addition amount of H2O2 was 9 ml L-1 (Figure 5). When the addition amount was more than 9 ml L-1, there was not direct relationship between two rates and H2O2 addition amount. This indicated that H2O2 not only was the generating agent of •OH but also the scavenger of •OH. The addition amount of H2O2 influenced the yield of ·OH and the removal of pollutant. Only in certain range, there was direct rel-ationship between the yield of •OH and H2O2 amount, and too much H2O2 could promote the clearance of •OH [34]. And the redundant H2O2 would enhance the effluent COD. So it was very necessary for waste-water to find the optimal addition amount of H2O2.

0102030405060708090

100

3 5 7 9 11 13

Rem

oval

rate

(%)

H2O2 additional amount (ml/L)


Figure 5. Effect of H2O2 addition amount on removal rate.

Influence of Illumination and aeration

Under the condition of illumination and aeration, the decolorization rate and COD removal rate were 73.85 and 65.17%, respectively (Figure 6). Without illumination or aeration, two rates were only 7.69 and 11.96%, respectively. Under the condition of only illu-mination, two rates were 53.52 and 42.12%, and under the condition of only aeration, two rates were 38.86 and 39.43%, respectively. So the removal rates

under the condition of illumination and aeration were higher than those under the condition of only illumin-ation or aeration. Illumination and aeration were two indispensable factors for photocatalytic reaction. When the energy of light was greater than the width of the forbidden band, the electrons in the valence band of TiO2 particles would transit to the conduction band and become the conduction band electrons, and leave a hole in the valence band. The hole was usu-ally captured by OH- and H2O. So the hydrogen and oxygen free radicals (•OH), which has strong ability of oxidation. When the electrons were captured by O2 adsorbed by the surface of TiO2 particles, many free radicals formed (O2

-·, HO2·, etc.), which participated in multiple redox process [35]. Due to addition of silicon in the composite film, the formation of Si-O-Ti key reduced the surface energy and the agglomeration of TiO2 reduced. The band-gap energy of the electrons of TiO2 from the valence band to the conduction band, so the photocatalytic ability of TiO2 raised.

01020304050607080

Illuminationand aeration

Illumination Setting Aeration

Rem

oval

rate

(%)


Figure 6. Effect of illumination and aeration on removal rate.

Orthogonal test of optimal process parameters

Based on the effects of varied factors on DDNP wastewater degradation, the mole ratio of Si and Ti in the TiO2/SiO2 composite film, chroma (initial concen-tration), pH, and H2O2 addition amount were selected as the orthogonal test factors. Each factor was taken three levels in the orthogonal test L9 (3

4). The range analysis was shown in Table 2.

Table 2. Range analysis of orthogonal test

NumberFactor

Mole ratio of Tiand Si (A)

Initial chroma (B)

pH (C) H2O2 addition amount (D)

K1 85.23 77.59 82.76 82.26

K2 85.71 79.52 79.71 80.41

K3 66.36 80.19 74.83 74.64

R 19.35 2.60 7.92 7.62


498

Table 2 is the result of range analysis of ortho-gonal test, and the decolorization rates were calcul-ated. The primary and secondary orders of different factors were defined by different range values in each column. The best level of each factor was determined by the maximum value of K (total of Kn of each factor at the same level). As a result, the optimum process parameters were determined. As could be seen from Table 2, the mole ratio of Ti and Si in the TiO2/SiO2 composite film had more impact on decolorization rate, whereas the initial chroma of DDNP wastewater had less impact on decolorization rate. The order of the effects of varied factors on photocatalytic degrad-ation is A > C > D > B. The optimal parameter was A2B3C1D1. Namely, the optimal parameters were 59:1 of mole ratio of Ti and Si, pH 1, 7ml L-1 H2O2 addition amount, and 3000 times chroma of DDNP waste-water. Under the optimal condition, the decolorization rate and COD removal rates were 98.50 and 92.50%, respectively. They were higher than any group. And they were far higher than those in the reaction cat-alyzed by pure TiO2 [16].

CONCLUSIONS

Many factors affected the photocatalytic activity of the filter media modified by TiO2/SiO2. The mole ratio of Ti and Si, pH, H2O2 addition amount and chroma of DDNP wastewater were researched. Under the optimal condition, the decolorization rate and COD removal rates are 98.50 and 92.50%, respec-tively. They were far higher than those in the reaction catalyzed by pure TiO2. The chroma and COD of effluent were 45 times and 22.89 mg L-1, which could meet the first class standard in the national Sewage Comprehensive Discharge Standard (GB8978-1996). This demonstrated that higher catalytic activity existed in the photocatalytic reaction under the opti-mal conditions determined by orthogonal test.

Acknowledgments

The authors are grateful to the Jiangsu Province Natural Scientific Foundation (BK2012159 and BK2011233), the Major Science and Technology Pro-gram for Water Pollution Control and Treatment (2012ZX07301001c), the College Students' Innova-tive Projects in Jiangsu Province (201410292044Y) and National Natural Science Foundation of China (41571471)for financial support of this work.

REFERENCES

[1] R.G. Jiang, Z.T. Liu, Initiating Explosive, Vol. 1, Ord-nance Industry Press of China, Beijing, 2006.

[2] M.H.V. Huynh, M.A. Hiskey, T.J. Meyer, M. Wetzler, PNAS 103 (2006) 5409-5412

[3] M.B. Talawar, R. Sivabalan, T. Mukundan, H. Muthu-rajan, A.K. Sikder, B.R. Gandhe, A.S. Rao, J. Hazard. Mater. 161 (2009) 589-607

[4] L.V. De Yong, G. Campanella, J. Hazard. Mater. 21 (1989) 125-133

[5] X.M. Song, H.E. Wang, G.X. Li, X.C. Zhang, Explosive Mat. 34 (2005) 36-38

[6] A.P. Zhou, Explosive Mat. 23 (1994)12-13

[7] X.G. Xi, H. Xiang, F.Y. Yu, J.R. Du, Y.X. Wang, Neimenggu Prev. Med. 23 (1998) 23-24

[8] Y.L. Wang, Q.F. Zhang, J. Gansu Univ. Technol. 29 (2003) 67-69

[9] S.B. Chen, X.C. Zhang, H.L. Xu, J. Xie, Environ. Pollut. Control 28 (2006)143-146

[10] X.M. Song, H.E. Wang, G.X. Li, X.C. Zhang, Explosive Mat. 34 (2005) 36-38

[11] H.X. Meng, B.B. Wang, S. Liu, R.Y. Jiang, H. Long, Ceram. Int. 39 (2013) 5785-5793

[12] L. Cui, F. Huang, M. Niu, L. Zeng, J. Xu, Y. Wang, J. Mol. Catal., A: Chem. 326 (2010) 1-7

[13] N.R. Khalid, Z. Hong, E. Ahmed, Y. Zhang, H. Chan, M. Ahmad, Appl. Surf. Sci. 258 (2012) 5827-5834

[14] L. Gu, Z.X. Chen, C. Sun, B. Wei, X. Yu, Desalination 263 (2010)107-112

[15] G.H. Liu, K.Y. Wang, N. Hoivik, H. Jakobsen, Sol. Energ. Mat. Sol., C 98 (2012 ) 24-38

[16] R.Y. Shen, G.Y. Feng, Y.T. Liang, X.Q. Zhao, W.Y. Zhang, Hem. Ind. 68 (2014) 809-818

[17] N. Mandzy, E. Grulke, T. Druffel, Powder Technol. 160 (2005) 121-126

[18] D.A.H. Hanaor, M.H.N. Assadi, S. Li, A.B. Yu, C.C. Sorrell, Comput. Mech. 50 (2012) 185-194

[19] K. Raj, B. Viswanathan, Indian J. Chem. 48 (2009) 1378- –1382

[20] C.N. Satterfield, Heterogeneous Catalysis Industrial Prac-tice, 2nd ed., McGraw-Hill, NewYork, 1991

[21] J. Herrmann, Catal. Today 53 (1999) 115-129

[22] F.R. Xiu, F.S. Zhang, J. Hazard. Mater. 172 (2009 ) 1458- –1463

[23] S. Chai, G. Zhao, Y. Zhang, Y.J. Wang, F.Q. Nong, M.F. Li, D.M. Li, Environ. Sci. Tech. 46 (2012) 10182-10190

[24] F. Shen, W. Que, Y. Liao, X. Yin, Ind. Eng. Chem. Res. 50 (2011) 9131-9137

[25] S. Wei, Q. Wang, J. Zhu, L. Sun, H. Lin, Z. Guo, Nano-scale 3 (2011) 4474-4502

[26] Q. Zhang, I. Lee, J. I. B. Joo, F. Zaera, Acc. Chem. Res. 46 (2013) 1816-1824.

[27] W. Li, D. Zhao, Adv. Mater. 25 (2013) 142-149.

[28] B. J. Jankiewicz, D. Jamiola, J. Choma, M. Jaroniec, Adv. Colloid Interface Sci. 170 (2012) 28-47.

[29] R. K. Iler, The Chemistry of Silica, Wiley-Interscience, NewYork, 1978.


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[30] W.Y. Zhang, H.D. Chen, Q.Y. Dong, X.J. Han, China Water Wastewater 25 (2009) 79-82

[31] C. Beck, T. Mallat, T. Buergi, A. Baiker, J. Catal. 204 (2001) 428-439

[32] C. Anderson, A. J. Bard, J. Phys. Chem. 101 (1997) 2611-2616

[33] Y.Z. Wang, Y. Yuan, H.X. Tang, Environ. Sci. 19 (1998) 2-5

[34] N.D. Zhang, J.L. Huang, W. Zheng, Tech. Equip. Environ. Pollut. Control 3 (2002) 20-22

[35] H.T. Zhu, Ind. Water Treat. 26 (2006) 53-55.

RONGYAN SHEN FANG LIU

TE LI XIA XU

YUTING LIANG XINGQING ZHAO

WENYI ZHANG

School of Environmental and Safety Engineering, Changzhou University,

Wujin District, Changzhou City, Jiangsu Province, China

NAUČNI RAD

TRETMAN OTPADNE VODE SA 2-DIAZO-4,6-DI-NITROFENOLOM POMOĆU TIO2/SIO2 KOMPO-ZITNOG FILMA U FOTOKATALITIČKOM REAKTORU

TiO2/SiO2 kompozitni film je korišćen za modifikaciju površine filtera koji je sinterovan otpadnim ugljem. Otpadna voda koja sadrži 2-diazo-4,6-dinitrofenol (DDNP) je korišćena za testiranje njegove fotokatalitičke aktivnosti u fotokatalitičkom reaktoru. U radu je ispitan uticaj odgovarajućih faktora na fotokatalitičku aktivnost modifikovanog filtera. Korišćenjem modifikovanog filtera postižu se stepen dekolorizacije od 70% i stepen smanjenja hemijske potrošnje kiseonika (HPK) merena preko DDNP od 60,85%. Nemodifikovani filter skoro da nema fotokatalitičku aktivnost. Ortogonalni eksperiment je pokazao da su optimalni opera-tivni parametri: odnos Ti/Si u kompozitnom filmu TiO2/SiO2 59:1, pH 1, 7 ml L-1 H2O2, i hroma 3000 puta (ekvivalentno početnoj koncentraciji DDNP u otpadnoj vodi). Pod ovim optimalnim uslovima posle 1 h fotokatalitičke reakcije, stepen obezbojenja i stepen ukla-njanja HPK odstranjivanja su dostigli vrednosti 98,50 i 92,50%, redom. Ako se primene ilu-minacija i aeracija, fotokatalitička aktivnost je veća nego pri primeni samo iluminacije ili samo aeracije.

Ključne reči: TiO2/SiO2, fotokataliza, modifikacija, DDNP, stepen dekolorizacije, HPK.




501

MILUTIN M. MILOSAVLJEVIĆ1

IVAN M. VUKIĆEVIĆ1 VEIS ŠERIFI1

JASMINA S. MARKOVSKI2

IVANA STOJILJKOVIĆ3

DUŠAN Ž. MIJIN4

ALEKSANDAR D. MARINKOVIĆ4

1Faculty of Technical Science, University of Priština, Kosovska

Mitrovica, Serbia 2Vinča Institute of Nuclear

Sciences, University of Belgrade, Belgrade, Serbia

3Faculty of Chemistry, University of Belgrade, Belgrade, Serbia 4Faculty of Technology and

Metallurgy, University of Belgrade, Belgrade, Serbia

SCIENTIFIC PAPER

UDC 628.3:547.495.2:543.42

DOI 10.2298/CICEQ141221006M

OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL AND N,N-DIALKYL THIOUREAS FROM WASTE WATER CONTAINING AMMONIUM THIOCYANATE

Article Highlights • Synthesis of N-alkyl and N,N-dialkyl thioureas are optimized in laboratory • The optimal laboratory synthesis of thioureas are transferred to semi-industrial level • Commercial as well as industrial waste materials are used in synthesis of thioureas • Presented methods are suitable environmentally benign option to existing procedures Abstract

The optimized methods for N-alkyl and N,N-dialkyl substituted thioureas synt-hesis starting from ammonium thiocyanates, waste water constituent from the production of tetramethylthiuram monosulfide (TMTS), and alkyl amine, are presented in this work., Thioureas synthesis was developed in two ways: Method I − reaction of the thiocyanate and alkylamine in the presence of hyd-rochloric acid; Method II − reaction of the thiocyanate with benzoyl chloride following by amine addition in the first step, and base hydrolysis in the second step. The structure of the synthesized compounds was confirmed by IR, 1H- and 13C-NMR and MS instrumental methods, and purity was determined by high-performance liquid chromatography method. It is shown that the proposed methods offer a high degree of conversion and purity of product, absence of by-products and technological applicability at industrial scale. Considering the importance of the tetramethylthiuram disulfide (TMTD) and TMTS as vulcani-zation accelerators as well as thiourea as the pharmacologically active com-pounds, it can be said that application of the optimized methods of thiourea synthesis will provide significant improvement in sustainable development and implementation of eco-friendly production technology. The described environ-mentally benign process of thioureas synthesis represents a suitable option to existing methods.

Keywords: thioureas, optimization, semi-industrial level, thiocyanate.

Thiourea (NH2CSNH2) and its derivatives, as well as oxidation products, found large alternative application in different industrial fields. Depending on the starting thiourea compound, used oxidants and pH value of reaction medium, a variety of oxidation products can be produced [1]. Catalytic oxidation by the use of hydrogen peroxide in presence of ruthe-nium complexes ethylenediaminetetra sulfate pro-

Correspondence: M.M. Milosavljević, Faculty of Technical Sci-ence, University of Priština, Knjaza Miloša 7, 38220 Kosovska Mitrovica, Serbia. E-mail: [email protected] Paper received: 21 December, 2014 Paper revised: 31 January, 2015 Paper accepted: 5 February, 2015

duce formamidine disulfide, thiourea dioxide, thiourea trioxide and sulfate [2]. Also, uses of hydrogen perox-ide as oxidative agent in reaction with thiourea pro-duces a powerful bleaching agent that has various applications in textile industry [3,4], and as corrosion inhibitors for industrial equipment such as boiler [5,6]. Solution of thiourea in dilute hydrochloric acid is used as a complexing agent for removing scales from boil-ers [7].

Synthesis of N-alkyl (aryl) and N,N-dialkyl thio-ureas, starting from the ammonium thiocyanate and an appropriate amine in water at 80–90 °C [8], was the first step in the overall procedure of obtaining certain 2-aminothiazole derivatives of 4-hydroxy-chromen-2- -one. This product was used as inhibitors of enzymes

M.M. MILOSAVLJEVIĆ et al.: OPTIMIZATION OF THE SYNTHESIS OF N-ALKYL… Chem. Ind. Chem. Eng. Q. 21 (4) 501−510 (2015)

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such as kinurenine-3-hydroxylase [9]. Also, N,N-dial-kyl-N'-alkyl thioureas may be prepared from dialkyl-amine and carbon disulfide in the presence of sodium hydroxide. The sodium salt of dialkyl dithiocarbamic acid was obtained in first reaction step, which by addi-tion of an alkyl amine, and extraction with methylene chloride, gives the corresponding thiourea product [10].

A large number of the methods of thiourea deri-vatives synthesis has been established: reaction of anilines and sodium isothiocyanate treated with tri-fluoroacetic acid [11], ammonium thiocyanate in the presence of concentrated hydrochloric acid [12], aroyl isothiocyanates with amines followed by basic hydro-lysis of α-aroyl-β-phenylthiourea product [13], tetra-isothiocyanatosilane with primary and secondary amines [14], thioureas with long chain alkyl amines at 170–180 °C, alkyl or aryl isothiocyanates with amine and carbon disulfide and amines [15]. Also, thiourea derivatives have been obtained by reaction of alkyl isothiocyanates with ammonia or amines [16], as well as reaction of carbon disulfide and primary amines in the presence of mercury acetate [17]. Reaction of disubstituted cyanamides with either hydrogen chlo-ride and LiAlHSH [18] or hydrogen sulfide in the pre-sence of ammonia [19] provided thiourea products. Recently, a new and efficient reagent 1-benzo-tri-azole-1-carbothioamide used for the preparation of mono and N,N-disubstituted thioureas was described. Nucleophilic displacement of benzotriazole from inter-mediary product by attack of a variety of amines gave corresponding N,N-disubstituted thioureas product [20].

Due to its extensive ligands applications in coor-dination chemistry, the chemistry, structure and potential applications of 1-(acyl/aroyl)-3-(mono-substi-tuted) and 1-(acyl/aroyl)-3,3-(di-substituted) thioureas have been overviewed recently [21]. A series of N-aroyl-N′-substituted thiourea derivatives have been prepared in good to excellent yields under the con-dition of solid-liquid phase transfer catalysis using polyethylene glycol-400 (PEG-400) as the catalyst [22]. Also, N-benzoyl-N'-carboxyl substituted thiourea derivatives have been synthesized by the reaction of benzoyl isothiocyanate with amino acids, and preli-minary biological tests showed excellent plant growth promotion activities [23]. Carbamoyl isothiocyanates can be used for synthesis of 1,3-disubstituted and 1,1,3-trisubstituted thiourea derivatives in reaction with alkyl or aryl amines. A secondary amine can be coupled to the carbamoyl thiourea using EDC (1-ethyl- -3-(3-dimethylaminopropyl)carbodiimide). This way, the formation of 1,3-disubstituted and 1,1,3-trisubsti-tuted guanidines through either stepwise or one-pot synthesis was achieved [24].

Several new thiourea and urea derivatives were prepared in satisfactory yield by the reaction of 4-amino-pyrazoles with substituted isothiocyanates or isocyanates in acetone [25]. In reaction of dimethyl-amine, carbon disulfide and hydrogen peroxide, an aqueous suspension of TMTD product was obtained [26,27]. Industrial process for the TMTS synthesis was performed by reaction of TMTD with cyanide ion and in such way ammonium thiocyanate was rel-eased according to the following reaction [28]:

TMTS was obtained as filtration cake while the collected filtrate was an aqueous solution of ammo-nium thiocyanate [29], which was chosen to be used as reactant for thioureas synthesis.

The aim of this work was focused on the opti-mization of N-alkyl and N,N-dialkyl thioureas syn-thesis starting from either commercial ammonium thiocyanate or waste water obtained from TMTS pro-duction which contains ammonium thiocyanate and corresponding amines. The first method developed in this paper, Method I, implied a reaction of thiocyanate with the appropriate amines and hydrochloric acid in ethyl acetate. Second method, Method II, was per-formed by thiocyanate treatment with benzoyl chlo-ride, amines and sodium hydroxide. In order to get highest reaction yield and purity of obtained product, optimization of presented procedures was performed with respect to variable reaction parameters: reaction time, temperature and molar ratio of reactants. The developed optimal technologies at the laboratory level were transferred and implemented at semi-industrial level with previously performed additional optimiz-ation of production technology in regards to reactant mole ratio.

EXPERIMENTAL

Two optimized methods (Method I and Method II) for the N-alkyl and N,N-dialkyl thioureas synthesis were developed at laboratory and semi-industrial level. The optimization of procedures was performed in relation to reaction time, temperature and mole ratio of reactant.


503

General procedure for the N-alkyl and N,N-dialkyl thiourea synthesis according to Method I

In a three-necked flask, equipped with magnetic stirrer, dropping funnel, condenser and thermometer, 10.0 ml of 20% water solution of ammonium thiocya-nate (0.12 mol) was introduced and heated to 90 °C. Appropriate amine, i.e., methyl amine (11.73 cm3, 0.10 mol) was added drop-wise with vigorous stirring of reaction mixture during one hour. Reaction took place for 3 h in temperature range 80–90 °C. Dilute hydrochloric acid (1:1) was added in a cooled reaction mixture and stirring was continued for 30 min. Reac-tion medium was subjected to vacuum for 5 min (10 kPa) followed by immediate addition of ethyl acetate (200 cm3) and 15 min intensive mixing. The reaction mixture (suspension) was filtered through a Buchner funnel and the ammonium chloride was separated as filtration cake. The upper layer of filtrate, ethyl acetate solution containing N-methyl thiourea, was separated from water layer, dried with sodium sulphate and sol-vent was removed by atmospheric distillation. Pure product was obtained by recrystallization from metha-nol followed by column chromatography purification (silica gel 60, 230–400 mesh) using benzene/metha-nol (9:1) as mobile phase. After solvent evaporation and product drying at 50 °C for 10 h, yield of N-methyl thiourea was 76.2%, melting point was 203.5 °C, and purity, obtained by HPLC analysis, was 98.9%. All other thioureas were synthesized in an analogous manner to the above described procedure and reac-tion conditions presented in Table 1.

General procedure for the N-alkyl and N,N-dialkyl thioureas synthesis according to Method II

In a three-necked flask equipped with magnetic stirrer, dropping funnel, condenser and thermometer, 8.5 ml of 20% water solution of ammonium thiocya-nate (0.10 mol) was introduced and heated to 45 °C. Benzoyl chloride (12.90 cm3, 0.11 mol) was added drop-wise with vigorous stirring of reaction mixture for two hours. After addition of the appropriate amount of alkyl amine reaction took place for 2 h at 45 °C and cooled down to room temperature. Carefully, 15 ml of sodium hydroxide solution (20%) was added to reac-tion mixture and continued with mixing for 30 min to provide hydrolysis of N-benzoyl-N,N-dialkyl thiourea. The reaction mixture was filtered through a Buchner funnel giving a filtration cake which contains raw pro-duct and collected filtrate of sodium benzoate water solution. Pure product was obtained by recrystalliza-tion from methanol followed by column chromato-graphy purification (silica gel 60, 230–400 mesh) using benzene/methanol (9:1) as a mobile phase. After solvent evaporation and drying at 50 °C for 10 h, N-methyl thiourea yield was 72.2%, melting point was 202-205 °C, and purity, obtained by performing HPLC analysis, was 98.5%. All other thioureas were syn-thesized in an analogous manner to above procedure, using the appropriate amine in regards to reaction conditions presented in Table 2.

Additionally, developed procedures were anal-ogously applied in the synthesis of thiourea deriva-tives starting from real waste water samples collected from the synthesis of TMTS at laboratory level. Cal-culation of the starting reaction mixture was based on the result of waste water composition: ammonium

Table 1. Reaction conditions, yield, melting point and purity of the product obtained according to Method I starting from model and real water

Product NH4SCN

(mol) Amine (mol)

Reaction timeh

Reaction temperature°C

Yield, %Melting point, °C

Found (reported) [lit.] Purity

(HPLC method)

Model water sample

CH3NHC(S)NH2 0.12 0.10 3.0-4.0 80-90 76.2 203.5 (202-203) [33] 98.9

(CH3)2NC(S)NH2 0.12 0.11 4.0-4.5 85-92 71.0 162-165 (163-164) [34] 98.3

EtNHC(S)NH2 0.12 0.10 3.0-4.0 82-88 75.8 111-112 (110-111) [35] 98.6

Et2NC(S)NH2 0.12 0.12 4.0-4.5 88-92 70.5 98-100 (99.2-100.6) [34] 98.7

PrNHC(S)NH2 0.12 0.10 3.0-4.0 81-86 73.2 108-110 (109) [36] 99.0

Pr2NC(S)NH2 0.12 0.12 4.0-5.0 88-92 70.0 109-110 [37] 98.8

Real water sample

CH3NHC(S)NH2 0.06 0.07 3.0-4.0 80-90 59.5 201-202 (202-203) [33] 97.2

(CH3)2NC(S)NH2 0.06 0.06 4.0-4.5 85-92 53.4 161-163 (163-164) [34] 97.3

EtNHC(S)NH2 0.06 0.07 3.0-4.0 82-88 51.8 110-112 (110-111) [35] 98.1

Et2NC(S)NH2 0.06 0.08 4.0-4.5 88-92 49.7 97-99 (99.2-100.6) [34] 98.0

PrNHC(S)NH2 0.06 0.06 3.0-4.0 81-86 54.6 106-108 (109) [36] 97.9

Pr2NC(S)NH2 0.06 0.07 4.0-5.0 88-92 47.3 107-109 [37] 97.5


504

thiocyanate 8.9%, sulfate 1.6%, phosphate 0.8% and cations (K, Na, Ca, Mg, Fe, etc.) in overall content of around 2.6%. Results of N-alkyl and N,N-dialkyl thio-urea synthesis are given in Tables 1 and 2. The struc-ture of the synthesized products was confirmed by IR, 1H- and 13C-NMR spectroscopic, and MS spectromet-ric data (Table 3).

Semi-industrial development of ammonium thiocyanate water solution treatment as by-product from TMTS production plant

A schematic presentation of the developed tech-nology at semi-industrial level for waste water treat-ment containing ammonium thiocyanate, obtained from TMTS production facility, is given in Figure 1.

Table 3. 1H- and 13C-NMR data, as well as results of elemental and IR analysis of N-alkyl and N, N-dialkylthioureas

Product 1H-NMR (δ / ppm) 13C-NMR (δ / ppm) Elemental analysis

Calculated/Found (%)

CH3NHC(S)NH2 2.71 (CH3), 7.46 (NH), 7.08 (NH2) 30.9 (CH3), 183.1 (CS) C 26.65; H 6.71; N 31.08; S 35.57

C 26.52; H 6.78; N 31.22; S 35.48

(CH3)2NC(S)NH2 3.05 (CH3), 7.10 (NH2) 31.3 (CH3), 182.9 (CS) C 34.59; H 7.74; N 26.89; S 30.78

C 34.64; H 7.78; N 26.95; S 30.63

EtNHC(S)NH2 1.19 (CH2-CH3), 3.51 (CH2-CH3), 7.49 (NH), 7.11 (NH2)

14.53 (CH2-CH3), 39.12 (CH2-CH3), 182.2 (CS)

C 34.59; H 7.74; N 26.89; S 30.78

C 34.54; H 7.71; N 26.80; S 30.95

Et2NC(S)NH2 1.03 (CH2-CH3), 3.13 (CH2-CH3), 7.11 (NH2)

12.83 (CH2-CH3), 41.37 (CH2-CH3), 181.6 (CS)

C 45.42. H 9.15. N 21.19; S 24.25

C 45.40; H 9.04; N 21.26; S 24.30

PrNHC(S)NH2 0.81 (CH2-CH2-CH3), 1.47 (CH2-CH2-CH3), 2.63 (CH2-CH2-CH3),

7.51 (NH), 7.10 (NH2)

10.93 (CH2-CH2-CH3), 21.55 (CH2-CH2-CH3), 43.75

(CH2-CH2-CH3), 181.4 (CS)

C 40.65; H 8.53; N 23.70; S 27.13

C 40.69; H 8.44; N 23.62; S 27.25

Pr2NC(S)NH2 0.78 (CH2-CH2-CH3), 1.31 (CH2-CH2-CH3), 2.11 (CH2-CH2-CH3),

7.12 (NH2)

11.78 (CH2-CH2-CH3), 21.05 (CH2-CH2-CH3), 53.75

(CH2-CH2-CH3), 180.53 (CS)

C 52.45; H 10.06; N 17.48; S 20.01

C 52.38; H 10.11; N 17.42; S 20.09

Product IR, νmax / cm-1 MS (m/z)

CH3NHC(S)NH2 3260, 3167 (NH, NH2), 2924, 2855, 1633 (NH2), 1557, 1465, 1300, 1152 (C=S), 1127

90

(CH3)2NC(S)NH2 3247 (NH2), 2935, 2865, 1628 (NH2), 1539, 1499, 1468, 1257, 1064 (C=S), 1048

104

EtNHC(S)NH2 3263, 3169 (NH, NH2), 2958, 2925, 2853, 1634 (NH2), 1554, 1464, 1302, 1155 (C=S), 1123

104

Table 2. Reaction conditions, yield, melting pint and purity of the product obtained according to Method II starting from model and real water

Product NH4SCN

(mol) PhCOCl

(mol) Amine (mol)

Reaction time, h

Reaction temperature°C

Yield%

Melting point, °C Found (reported) [lit.]

Purity (HPLC method)

Model water sample

CH3NHC(S)NH2 0.10 0.11 0.11 4.0-5.0 40-45 72.2 202-205 (202-203) [33] 98.5

(CH3)2NC(S)NH2 0.11 0.10 0.12 5.0-5.5 45-55 68.3 161-164 (163-164) [34] 98.7

EtNHC(S)NH2 0.10 0.11 0.11 4.0-4.5 40-45 72.5 109-111 (110-111) [35] 98.6

Et2NC(S)NH2 0.10 0.12 0.12 5.0-6.0 50-60 67.8 97.5-99.0 (99.2-100.6) [34] 98.9

PrNHC(S)NH2 0.10 0.11 0.11 4.0-5.0 45-55 71.3 108-111 (109) [36] 99.0

Pr2NC(S)NH2 0.10 0.12 0.13 5.5-6.0 55-65 66.7 110-111 [37] 98.9

Real water sample

CH3NHC(S)NH2 0.05 0.07 0.07 4.0-5.0 40-45 54.7 200-202 (202-203) [33] 97.1

(CH3)2NC(S)NH2 0.06 0.06 0.06 5.0-5.5 45-55 48.6 160-163 (163-164) [34] 98.0

EtNHC(S)NH2 0.05 0.07 0.07 4.0-4.5 40-45 49.5 108-110 (110-111) [35] 97.6

Et2NC(S)NH2 0.05 0.08 0.08 5.0-6.0 50-60 51.2 97-99 (99.2-100.6) [34] 98.2

PrNHC(S)NH2 0.05 0.07 0.07 4.0-5.0 45-55 50.7 105-108 (109) [36] 98.2

Pr2NC(S)NH2 0.05 0.08 0.08 5.5-6.0 55-65 42.8 108-111 [37] 97.2


505

Table 3. Continued

Product IR, νmax / cm-1 MS (m/z)

Et2NC(S)NH2 3275, 3174 (NH2), 2938, 2867, 1630 (NH2), 1532, 1493, 1461, 1254, 1061 (C=S), 1045

132

PrNHC(S)NH2 3165 (NH, NH2), 2920, 2851, 1638 (NH2), 1543, 1462, 1300, 1163 (C=S), 1115 (C=S)

118

Pr2NC(S)NH2 3277 (NH2), 2939, 2866, 1631 (NH2), 1529, 1492, 1459, 1250, 1060 (C=S), 1039 (C=S)

160

Figure 1. Schematic presentation of semi-industrial production technology of N-alkyl and N,N-dialkyl thioureas.

TMTS is produced by heterolytic cleavage of disulfide bridge present in TMTD by nucleophilic attack of cyanide ion introduced by potassium cya-nide in the presence of ammonium chloride as an pH controlling agent (provide pH of reaction mixture in the range 6-7). In the course of the production of TMTS, waste water containing by-product ammonium thiocyanate is inevitably generated. Method for the processing of waste water included filtration and tran-

sport to reactor 3 (6 m3). Treatment of waste water by the Method I was performed by the addition of alkyl amine and hydrochloric acid (Table 4), vacuum treat-ment (10 KPa) for 10 min and ethyl acetate intro-duction into reaction mixture. After stirring of reaction mixture at 80–90 °C for 3 h, obtained suspension was filtered through a Buchner funnel (position 4). The filtration cake contained technical ammonium chloride and after purification and drying it could be used as


506

commercial product. Filtrate was consisted from two layers: upper one contained dissolved product in ethyl acetate and lower one was water layer which con-tained mostly inorganic salts. After separation from water layer, upper layer was dried and subjected to atmospheric distillation to remove ethyl acetate, fol-lowed by vacuum distillation applied to evacuate resi-dual solvent and higher boiling materials (position 5). Satisfactory quality for commercial application was achieved by recrystallization (position 6) from metha-nol producing 140.6 kg (51.4%) and 96.1% purity of N-ethyl thiourea, obtained by HPLC analysis (Table 4).

Production of N-ethyl thiourea (Method II) was performed by transferring the waste water, containing ammonium thiocyanate, into reactor 7 following by addition of benzoyl chloride and alkyl amine (Table 4). The reaction took place for 2 h at 45 °C, after what reaction mixture was cooled down to room tempera-ture. Addition of 0.51 m3 (20%) sodium hydroxide and continuation of the mixing for 30 min provided hyd-rolysis of N-benzoyl-N-ethyl thiourea (position 8). The reaction mixture was filtered through a Buchner fun-nel, the water solution of sodium benzoate was col-lected and filtration cake contained raw product. The raw product was purified by double recrystallization from methanol (position 6) producing 144.0 kg (52.7%) of N-ethyl thiourea (HPLC purity 95.9%) (Table 4). Analogous synthesis of N,N-diethyl thiourea was performed at semi-industrial level (Table 4).

Instrumental techniques used for structure determination of synthesized compounds

1H- and 13C-NMR measurements were performed on a Varian Gemini 2000 (200/50 MHz) instrument at 25 °C. Chemical shifts (δ) were reported in part per million (ppm) relative to tetramethylsilane (δH = 0 ppm) in 1H-NMR, and to deuterated chloroform (δC = = 77.2 ppm) in 13C-NMR, using the residual solvent peak as a reference standard. Fourier-transform infrared (FTIR) spectra were recorded in transmission mode using a BOMEM (Hartmann & Braun) spectro-meter. All mass spectra were recorded on a Thermo Finnigan Polaris Q ion trap mass spectrometer, inc-luding TraceGC 2000 (ThermoFinnigan Corp., Austin, TX, USA). Polaris Q ion trap GC/MS system with EI and DIP (direct insertion probe) techniques was used. DIP mode was used to introduce the sample and EI/MS technique to acquire the spectra. The ion-ization conditions were: ion source temperature 200 °C, maximum energy of electron excitation 70 eV, corona current 150 μA. The data obtained were pro-cessed using XcaliburTM 1.3 software. HPLC (high performance liquid chromatograph) was performed on Spectra System P4000 equipped with a UV detector, Zorbax SB-C8 column, mobile phase benzene/metha-nol (HPLC grade) (9:1), isocratic mode. Elemental analysis was performed on the Vario EL III elemental analyzer, and the results of analysis are in good agreement with theoretical values (±0.2%).

The concentration of starting ammonium-thio-cyanate in waste water was determined according to two methods: the Vollhard method [30], and method

Table 4. Results of of N-ethyl and N,N-diethyl thiourea synthesis performed at semi-industrial level; reactant: EtNH2 (70%, ρ = 0.88 g/cm3, HCl (15%, ρ = 1.01 g/cm3), EtOOCCH3 (ρ = 0.89 g/cm3), MeOH ( ρ = 0.80 g/cm3), PhCOCl (ρ = 1.21 g/cm3), NaOH (20%, ρ =1.2 g/cm3); Et2NH (98.5%, ρ = 0.71 g/cm3, HCl (15%, ρ = 1.01 g/cm3), EtOOCCH3 (ρ = 0.89 g/cm3) MeOH ( ρ = 0.80 g/cm3), PhCOCl (ρ= 1.21 g/cm3), NaOH (20%, ρ = 1.2 g/cm3)

Batch/ method

Reactant Reaction condition

By-product Product

Waste water (m3)

Ethyl amine (m3)

HCl (m3)

Ethyl acetate

(m3)

MeOH m3

ArCOCl m3

NaOH m3

Timeh

Tempera-ture, °C

NH4Cl kg

ArCOOH m3

Yield kg

Yield %

Purity HPLC

Melting point, °C

N-Ethyl thiourea

1/Method I 1.0a 0.19 0.07 0.60 0.80 - - 5.0 80-90 96.0 - 140.6 51.4 96.1 111-113b

2/Method I 1.0a 0.23 0.08 0.60 0.80 - - 5.1 80-90 99.0 - 153.7 56.2 96.3 110-112b

3/Method II 1.0a 0.19 - - 0.80 0.32 0.51 6.0 45-55 - 0.5c 144.0 52.7 95.9 110-111b

N,N-Diethyl thiourea

1/Method I 1.0a 0.27 0.08 0.60 0.85 - - 5.5 85-90 95.5 - 134.7 49.3 96.1 97-99d

2/Method I 1.0a 0.32 0.08 0.60 0.85 - - 5.7 85-90 98.5 - 137.0 50.4 96.5 98-100d

3/Method II 1.0a 0.27 - - 0.85 0.33 0.55 6.5 55-60 - 0.45c 124.5 45.6 96.3 97-100d

1/Method I 1.0a 0.27 0.08 0.60 0.85 - - 5.5 85-90 95.5 - 134.2 49.1 96.0 97-99d

aQuantity of ammonium thiocyanate in waste water - 200 kg (20% water solution); bliterature value of melting point of EtNHC(S)NH2 is 110-111 °C [35]; ccollected ArCOOH in water solution (concentration 40%); dliterature value of melting point of Et2NC(S)NH2 is 97-99 °C (99.2-100.6 °C) [34]


507

based on thiocyanate reaction with thioglycolic acid which provide quantitative conversion to N-substi-tuted thiocarbamoylmercaptoacetate or 3-substituted rhodamine, a product with characteristic UV absorp-tion [31]. Determination of cations concentrations in water solution from TMTS semi-industrial production plant was performed by the use of inductively coupled plasma mass spectrometry (ICP-MS) using an Agilent 7500ce ICP-MS system (Waldbronn, Germany) and Perkin Elmer Analyst 200, MHS 15 (Waltham, MA, USA). ICP-MS was equipped with an octopole colli-sion/reaction cell, Agilent 7500 ICP-MS ChemStation software, a MicroMist nebulizer and a Peltier cooled (2.0 °C) quartz Scott-type double pass spray cham-ber. Standard optimization procedures and criteria are specified in the manufacturer’s instruction manual. Sulfate was determined by using standard gravimetric method, and phosphate by spectrophotometric method according to the Deniges procedure [32].


In the experimental part of this work, optimal parameters for N-alkyl and N,N-dialkyl thioureas syn-thesis (Methods I and II - Experimental) were pos-tulated. In both methods a model and waste water containing ammonium thiocyanate (the latter one is obtained during the synthesis of TMTS) were used in reaction with corresponding amine. Optimal condi-tions for N-alkyl and N,N-dialkyl thioureas synthesis were selected on the basis of maxima yield and purity of the product in relation to variable reaction para-meters: reaction time, temperature and molar ratio of reactants. The obtained optimal results of N-alkyl and N,N-dialkyl thioureas synthesis are presented in Tables 1 and 2.

Based on the results given in Tables 1 and 2, it can be observed that high yields and purity of syn-thesized N-alkyl and N, N-dialkyl thioureas are achieved starting from model and waste water con-taining ammonium thiocyanate. General consider-ation of the presented results clearly indicates some-what higher yields obtained by the use of model water. Such result is obviously a consequence of the presence of interfering ions, which could have a det-rimental effect on the reaction yield. The structure of synthesized products was confirmed by IR, 1H-NMR and MS spectrometric data (Table 3).

From the reaction yield and purity of the obtained product, shown in Table 1, it can be con-cluded that an increase of the amount of the second-ary amine over 0.12 mol have no influence on the yield and purity of the synthesized N-alkyl and N,N-

-dialkyl thioureas. It may be noted that with the use of secondary alkyl amines, at equimolar ratio of reac-tants, a negligible increase of the product yield from 70.0 to 71.0% is obtained. Also, it is interesting that if the primary alkyl amine is used, wherein the thiocya-nate is in excess, the yield is in the range from 73.2 to 76.2%. Thus, it can be deduced that the higher yield is obtained by reaction of the primary amine with ammonium thiocyanate, while the lowest yield is obtained using dipropylamine as reactant. The longer reaction time, more than six hours, and an reaction temperature increase does not give a higher yield of N,N-dialkyl thiourea (Method I).

Based on the data presented in Tables 1 and 2, higher yields of N-alkyl and N,N-dialkyl thioureas obtained following Method I could be assumed. Simi-lar influences of amine structure on reaction yields is obtained by comparing Methods I and II, while the lowest yield for dipropyl amine (70.0% by Method I and 66.7% by Method II) is observed (Tables 1 and 2). Also, longer reaction time and higher temperature are applied for reaction performed in presence of di-substituted amines.

Analysis of the experimental data indicates that influence of structural features of reacting species, i.e. amine effect on the yield of N-alkyl and N,N-dialkyl-thioureas, could be discussed. Considering stereo-chemical aspect of amine involved in creation of acti-vated complex indicate a significant influence of the steric effect of the amine alkyl group on the stability of activated complex. The lower yield found in reactions with disubstituted alkyl amines is an indication of the existence of more pronounced repulsive steric inter-action of the alkyl groups in the activated complex. More intensive steric repulsion of voluminous alkyl groups presented in the disubstituted amine cause decreasing of the ability of the amine to access to the reaction center, i.e., electrophilic carbon of thiocya-nate group. Reduced effectiveness of the amine group to exert a nucleophilic attack caused a dec-rease in reaction yield. The higher reaction yield of thiourea product obtained by Method I, in comparison to Method II, could be reasonably explained by com-plexity of the reaction mechanism, due to high reac-tivity of benzoyl chloride and ability of N-benzoyl-N,N- -dilakyl thiourea to participate in a side reaction (Figure 2). It can be assumed that Method I takes place as a one-step reaction by nucleophilic addition of amine at the thiocyanate group, while in Method II, a multistep reaction mechanism is operative. Nucleo-philic attack of the thiocyanate anion to the carbonyl group of benzoyl chloride occurs in the first step of reaction mechanism following by an attack of the


508

amine on the thiocarbonyl carbon of the obtained benzoyl thiocyanate in the second step. Basic hydro-lysis of the intermediary compound produce benzoic acid and N-alkyl and N,N-dialkyl thioureas product (Figure 2).

The probable reaction mechanisms of the N- -alkyl and N,N-dialkylthioureas synthesis performed by Method I [8], and Method II, over benzoylthio-cyanate intermediary compound and N-benzoyl-N,N-dilakyl thiourea [13], are presented in Figure 2.

Semi-industrial synthesis of N-ethyl and N,N-diethyl thiourea

Based on the laboratory results of waste water treatment containing thiocyanate from the synthesis of the TMTS (Methods I and II), we transferred deve-loped laboratory technology to semi-industrial level. The described technological procedure of waste water treatment in the production of the TMTS actu-ally represents a new technological process for the alkyl tioureas synthesis using waste water from the production of the TMTS and the TMTD, which con-tains the ammonium thiocyanate. The results of semi-industrial synthesis of N-ethyl and N,N-diethyl thio-urea, from ammonium thiocyanate present in the

waste water from the production plant of TMTS, are summarized in Table 4.

The defined synthetic procedure, Method I, is applied in Batches 1 and 2 (Table 4). In comparison to Batch 1, where the thiocyanate excess of the 20% is used and 51.4% yield is achieved, equimolar ratio of the reactants increased yield to 56.2% in Batch 2. However, as a result of Method II, reaction yield of Batch 3 is lower than Batch 2, where Method I is used. Identical reaction conditions presented in Table 4 are applied in a pilot-plant production of N,N-diethyl thiourea (Table 4). It can be seen that the lower yields is achieved in all three batches with N,N-diethyl thio-urea in regards to the yields of pilot-plant synthesis of N-ethyl thiourea (Table 4). On the basis of the results obtained by the semi-industrial production process it can be concluded that a) wastewater from the pro-duction TMTS's can be treated in two ways, b) signi-ficant conversion is achieved (over 45%) in all of the three batches shown in Table 4 and the final com-mercial products of N-ethyl and N,N-diethylthiourea are the high level of purity determined by the HPLC method, c) the structure of the isolated components and all of the synthesized products are confirmed by instrumental methods.

Figure 2. Proposed mechanisms of N-alkyl and N,N-dialkyl thioureas synthesis performed according to Method I and II.


509

Developed optimal methods offers good alter-native technology for industrial exploitation in pro-duction of N-alkyl and N,N-dialkylthiourea from com-mercial ammonium thiocyanate, or more preferably from waste water containing this reactant obtained from TMTS production plant. From an ecological point of view, both facts related to use waste water as the reaction medium and by-product ammonium thiocya-nate as reagent in the synthesis of N-alkyl and N,N- -dialkyl thioureas, indicate that such technology is highly favorable to be implemented at semi-industrial level. These environmentally friendly and simple pro-cesses, with short reaction times, represent a suitable option to existing methods. This concept contributes to the remarkable effectiveness and economic benefit of the implemented optimal laboratory procedure at the semi-industrial level.

CONCLUSION

The results presented in this work describe an optimal procedure for the laboratory and semi-indus-trial synthesis of N-alkyl and N,N-dialkyl thioureas. The developed processes, presented by Method I and Method II, start from either model or waste water containing ammonium thiocyanate. High purity and satisfactory yield of N-alkyl and N,N-dialkyl thioureas synthesis were obtained by applying optimal Methods I and II in both laboratory and semi-industrial level. Based on the high degree of conversion and purity of the obtained compounds it was possible to perform transfer (scale-up) of the optimal laboratory synthesis of N-alkyl and N,N-dialkyl thioureas to semi-industrial level. The new procedure of the optimal N-alkyl and N,N-dialkyl thioureas achieves significant improve-ments in terms of product yield and purity, process duration and simplicity as well as low impact to the environment. These results strongly indicate the use-fulness of the presented methods for synthesis of thiourea derivatives starting from commercial as well as industrial waste material.

Acknowledgements

This study was carried out within the project “Exploring the impact of climate change on the living environment: monitoring of impact, adaptation, miti-gation” (43007) funded by the Ministry of Education and Science of the Republic of Serbia in the frame-work of integrated and interdisciplinary research inc-luding the period 2011-2015 year.

REFERENCES

[1] S. Sahua, P. Sahooa, S. Patelb, B. Mishraa, J. Sulfur Chem. 32 (2011) 171–197

[2] D. Chatterjee, S. Rothabart, R. Eldik, Dalton Trans. 42 (2013) 4725-4729

[3] M. Arifoglu, W. Marmer, R. Dudley, Text. Res. J. 62 (1992) 94–100

[4] J. Cagarra, J. Gacen, M. Caro, M. Pepio, J. Soc. Dyers Colour. 104 (1988) 273–279

[5] J. Ayres, Decontamination of Nuclear Reactors and Equipment, Ronald Press Co., New York, 1970, p. 177

[6] H. Klern, J. Lux, D. Noll, W. Reider, H. Phillips, A Field Survey of Internal Boiler Tube Corrosion in High-Pres-sure Utility Boilers, in Proceedings of the American Power Conference, Illinois Institute of Technology, Chi-cago, IL, 1971, p. 702

[7] J. Knox, J. Smith, R. Stout, US 3730901 (1973)

[8] N. Vuković, S. Sukdolak, S. Solujić, T. Milošević, Arch. Pharm. Chem. Life Sci. 341 (2008) 491–496

[9] S. Rover, M. Cesura, P. Huguenin, A. Szente, J. Med. Chem. 40 (1997) 4378–4385

[10] R. Maddani, K. Prabhu, J. Org. Chem. 75 (2010) 2327- -2332

[11] B. Loev, P. Bender, H. Bowman, A. Helt, R. McLean, T. Jen, J. Med. Chem. 15 (1972) 1024-1027

[12] F. Kurzer, Organic Syntheses, Collective Volume 4, N. Rabjohn Ed., John Wiley & Sons, Inc., New York, 1963, p. 180

[13] C. Rasmussen, F. Villani, L. Weaner, B. Reynolds, A. Hood, L. Hecker, S. Nortey, A. Hanslin, M. Costanzo, E. Powell, A. Molinari, Synthesis (1988) 456-459

[14] R. Neville, J. McGee, Organic Syntheses, Collective Vol-ume 5, H.E. Baumgarten Ed., John Wiley & Sons, Inc., New York, 1973, p. 801

[15] J. Erickson, J. Org. Chem. 21 (1956) 483-484

[16] W. Fathalla, P. Pazdera, Arkivoc 1 (2002) 7-11

[17] J. Bernstein, H. Yale, K. Losee, M. Holsing, J. Martins, W. Lott, J. Am. Chem. Soc. 73 (1951) 906-912

[18] M. Koketsu, Y. Fukuta, H. Ishihara, Tetrahedron Lett. 42 (2001) 6333-6335

[19] H. Cressman, Organic Syntheses, Collective Volume 3, E. C. Horning Ed., John Wiley & Sons, Inc., New York, 1955, p. 608-609

[20] A. Katritzky, N. Kirichenko, B. Rogovoy, J. Kister, H. Tao, Synthesis (2004) 1799-1805

[21] A. Saeed, U. Florke, M. Erben, J. Sulfur Chem. 35(3) (2014) 318-355

[22] Y. Zhang, T. Wei, Li-M. Gao, Synthetic Commun. 31 (2001) 3099-3105.

[23] Z. Li, Y. Zhang, Y. Wang, Phosphorus Sulfur Silicon Relat. Elem. 178 (2003) 293-297

[24] B. Linton, A. Carr, J. Org. Chem. 65 (2000) 1566-1568

[25] B. Kaymakçıoglu, S. Rollas, Eur. J. Pharm. Sci. 26 (2005) 97–103.


510

[26] M. Milosavljević, A. Marinković, J. Marković, D. Brković, M. Milosavljević, Chem. Ind. Chem. Eng. Q. 18 (2012) 73-81

[27] A. Marinković, M.Milosavljević, D. Milenković, G. Ivano-vić, Chem. Ind. Chem. Eng. Q. 14 (2008) 251−255

[28] M. Milosavljević, Magistarski rad, Tehnološko–metalurški fakultet, Beograd, 1991

[29] M. Milosavljević, M. Milosavljević, D. Mijin, S. Petrović, Novel technologies and economic development, in Book of abstracts of 10th Symposium, Faculty of Technology, Leskovac, 2013, p. 138

[30] H. Laitinen, Chemical Analysis, McGraw-Hill, New York, 1960

[31] Ĺ. Drobnica, W. Knoppová, Chem. Zvesti 27(6) (1973) 799-780

[32] S. Yuen, A. Pollard, J. Sci. Food Agr. 6(4) (1955) 223-229

[33] V. Dovlatyan, Izv. Akad. Nauk Armyan. SSR, Khim. Nauki 16 (1963) 565-569

[34] H. Takahashia, A. Nishinaa, R. Fukumotoa, H. Kimurab, M. Koketsuc, H. Ishiharad, Life Sci. 76 (2005) 2185–2192

[35] M. Muhammad, Transit. Metal Chem. 36 (2011) 505-512

[36] N. Vijayakumaran, J. Indian Chem. Soc. 40 (1963) 953- –956

[37] H. Hartmann, I. Reuther, J. Prakt. Chem. 315 (1973) 144- –148.

MILUTIN M. MILOSAVLJEVIĆ1

IVAN M. VUKIĆEVIĆ1 VEIS ŠERIFI1

JASMINA S. MARKOVSKI2

IVANA STOJILJKOVIĆ3

DUŠAN Ž. MIJIN4

ALEKSANDAR D. MARINKOVIĆ4 1Fakultet Tehničkih Nauka, Univerzitet

u Prištini, Kosovska Mitrovica, Srbija 2Institut za Nuklearne nauke Vinča,

Univerzitet u Beogradu, Beograd, Srbija

3Hemijski Fakultet, Univerzitet u Beogradu, Beograd, Srbija

4Tehnološko-Metalurški fakultet, Univerzitet u Beogradu, Beograd,

Srbija

NAUČNI RAD

OPTIMIZACIJA POSTUPAKA SINTEZE N-ALKIL- I N,N-DIALKILTIOUREA IZ OTPADNE VODE KOJA SADRŽI AMONIJUM-TIOCIJANAT

Optimizovane metode za sintezu N-alkil- i N,N-dialkiltiourea, koje polaze iz amonijum--tiocijanata, koji se nalazi u otpadnoj vodi iz proizvodnje tetrametiltiuram-monosulfida (TMTS), i alkilamina, prikazane su u ovom radu. Osvojene su dve metode sinteze tiouree: Metoda I − reakcija tiocijanata u prisustvu hlorovodonične kiseline; Metoda II − reakcija tiocijanata sa benzoil-hloridom nakon čega sledi dodavanje odgovarajućeg amina u prvom koraku, i bazne hidrolize inermedijera u drugom koraku. Struktura sintetisanih tiourea je potvrđena na osnovu podataka iz IR, 1H- i 13C-NMR, kao i MS spektara, a čistoća je potvrđena primenom metode tečne hromatografije pod visokim pritiskom. Pokazano je da se primenom optimalnih metoda dobijaju visoki prinosi i čistoća proizvoda, a usled odsus-tva sporednih proizvoda metode su primenjive na industrijskom nivou proizvodnje. Uzi-majući u obzir značaj tetrametiltiuram-disulfida (TMTD) i TMTS kao ubrzivača vulkanizacije i tiouree kao potencijanih farmakološki aktivnih jedinjenja, može se konstatovati da će primena optimizovanih metoda sinteze tiouree obezbediti značajna poboljšanja u primeni zelenih tehnologija u proizvodnoj praksi, kao i doprineti održivom razvoju. Opisani procesi sinteze tiourea imaju mali uticaj na životnu sredinu i zbog toga predstavljaju prihvatljive opcije za primenu u odnosu na postojeće metode sinteze tiourea.

Ključne reči: tiourea, optimizacija, polu-industrijski nivo proizvodnje, tiocijanat.




511

SHENG FANG LI-PING WANG

TING WU

School of Food Science and Biotechnology Engineering,

Zhejiang Gongshang University, Hangzhou, China

SCIENTIFIC PAPER

UDC 633.685(510):66.047.4/.6:51

DOI 10.2298/CICEQ140816007F

MATHEMATICAL MODELING AND EFFECT OF BLANCHING PRETREATMENT ON THE DRYING KINETICS OF CHINESE YAM (Dioscorea opposita)

Article Highlights • Drying kinetics of Chinese yam slices are investigated • Effects of blanching pretreatment on drying kinetics • Six thin layer drying models are compared • The effective diffusivities and activation energy are obtained Abstract

The effects of blanching pretreatment on the drying kinetics of Chinese yam (Dioscorea opposita) slices were investigated. Drying experiments were car-ried out at 60, 70, 80 and 90 °C. Six thin layer models were evaluated and the coefficient of determination (R2), chi-square (χ2), and root means square error (RMSE) were used to analyze the model performance for both raw and blanched samples. The Wang and Singh model gave best results with R2 of 0.9987 and RMSE of 0.0136 for raw yam slices, and R2 of 0.9989 and RMSE of 0.0119 for blanched samples. The effective moisture diffusivity coefficient Deff varied in the range of 0.7295×10-9 to 2.4087×10-9 m2 s-1 for raw slices, and 1.3748×10-9 to 3.8524×10-9 m2 s-1 for the blanched ones. The activation ener-gies of yam slices drying were 41.149 and 33.499 kJ mol-1 for raw and blanched yam slices, respectively. The results show that blanching pretreatment can reduce the total drying time and improve the effective moisture diffusivity com-pared to the raw samples.

Keywords: Chinese yam, hot air drying, kinetics, modeling, blanching.

The Chinese yam (Dioscorea opposita), called “Shan Yao” (which means “mountain medicine”) in Chinese herbalism, has a long history of cultivation in China and Eastern Asia for its edible tuber [1]. The yam tuber is also a traditional ingredient of herbs that prescribed in Chinese herbalism to treat diseases like nephritis, hyperthyroidism and diabetes [1]. It contains a large amount of water, similar to fruits, and can be eaten raw or cooked before consumption. The dried yam slices can be served fried, roasted and boiled, used as an ingredient in herbs and for the production of yam starch [2].

Correspondence: S. Fang, School of Food Science and Bio-technology Engineering, Zhejiang Gongshang University, Hang-zhou 310018, China. E-mail: [email protected] Paper received: 16 August, 2014 Paper revised: 29 January, 2015 Paper accepted: 19 February, 2015

Drying is one of the most important preservation processes commonly used for food products that are easily deteriorated [3]. As a simple postharvest tech-nology, drying can prolong the shelf life of food pro-ducts, and reduction in volume and weight in favor of transportation. Drying can also preserve food quality by lowering their water activity, thus avoiding con-tamination and spoilage during transportation and sto-rage. Convective drying by hot air is a common tech-nology for food postharvest processing because of its large scalability and easy to performance [3,4]. How-ever, hot air drying is a high energy consumption process. It is a complex process containing both the heat and mass transfer where water is transferred from the inside of food materials to the outside atmo-sphere by diffusion, which is very slow. The total energy consumption in hot air drying process dep-ends on many parameters such as pretreatments, drying temperature drying time and air velocity [4,5].

S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING… Chem. Ind. Chem. Eng. Q. 21 (4) 511−518 (2015)

512

High drying temperature may shorten the drying time, however, it can bring disadvantages such as color deterioration and nutrients degradation [5,6]. Pre-viously, many investigations have explored the effects of different drying parameters, including drying tem-perature, air velocity, relative humidity and sample thickness on the drying characteristics of agricultural and food products, such as bottle gourd [7], Chinese jujube [8], carrots [9], sweet potatoes [10,11] and pumpkins [12].

Meanwhile, many pretreatments methods are employed in order to mitigate quality attributes deg-radation [3,6]. They can also reduce the total drying time, which is more energy efficient and generate final products with good quality. Many natural or synthetic chemicals are used for dipping pretreatments prior to drying such as ascorbic acids [13], potassium meta-bisulphide and alkaline ethyl oleate [14]. Alternatively, raw foods and vegetables can also be pretreated by thermal methods such as hot water blanching prior to drying. Generally, thermal blanching is carried out by exposing samples either at low temperature for a long time (LTLT) or high temperature for a short time (HTST). Blanching is the most commonly used thermal pretreatments before processing of agricul-tural products as it can destroy enzymes, which cause deterioration reactions, off-flavour and undesir-able changes in color, texture and nutrients [15]. In addition, blanching can also enhance drying rate by expelling intercellular air from the tissues, softening the texture or by dissociating the wax on the products skin [16,17].

Mathematical modeling and simulation of the drying kinetics of food products is an important tool for designing novel drying systems, drying equipment and minimize operative energy consumption [3]. Rec-ently, several studies have been conducted on the experimental and mathematical modeling of the dry-ing characteristics of various food products, like tom-ato slices [18,19] and peach slices [20]. Compre-hensive review [3] on the subject of mathematical models on convective drying of different agricultural and food materials is available. Some studies have been published concerning the drying process of yam [2,21-23]. However, some of them were concerning about the drying process of yam starch [2]. Xiao et al. [21] investigated the effect of superheated steam blanching on the drying kinetics and quality of yam slices under air impingement drying. Lin et al. [22] studied the dehydration of yam slices by using FIR- -assisted freeze drying. Sobukola et al. [23] studied the convective hot air drying at temperature 70, 80 and 90 °C of blanched yam slices (Dioscorea rotun-

data) under LTLT condition and have not compared with the raw yam slices. According to our best know-ledge, the effects of temperature and steam blanching on the dry characteristics and its modeling for Chin-ese yam (Dioscorea opposita) slices have not been reported.

The objective of this study was to: a) investigate the effect of air temperatures and steam blanching pretreatment on the drying time and b) fit the expe-rimental drying data of yam slices to several mathe-matical models available in literatures and evaluate a suitable model to describe the process. Four tempe-ratures 50, 60, 70 and 80 °C were investigated and six equations were compared. The effective moisture diffusivities at different drying temperatures for blanched and untreated yam slices were estimated from Fick’s law. Furthermore, the activation energy was estimated from the Arrhenius equation.


Materials

Chinese yams (Dioscorea opposita) were pur-chased from a local supermarket (Hangzhou Wumart Supermarket) in Hangzhou, China. They were sel-ected by homogeneous diameter as well as the abs-ence of physical damage. The yams were washed by tap water and put into a refrigerator at about 4 °C for storage before usage.

Experimental apparatus

The drying experiments were performed in a continuous convective dryer as described previously by Meng et al. [24]. It is composed of a heater, blower, square air tunnel and other temperature instruments and is shown in Figure 1. The air was sucked by the blower and heated to the desired temperature automatically by regulating voltage to the heaters inside the air channel. The air velocity is con-trolled by a revolution speed regulator. A digital elec-tronic balance (Model BS124S, Beijing Sartorius ins-trument system Co., LTD., China) with an accuracy of 0.01 g and a range of 0-210 g was used to conti-nuously measure the moisture loss of samples. The values shown in the electronic balance were moni-tored by a camera connected to a computer for rec-ording.

Experimental procedures

Yams were cut into cylindrical slices homogen-eously with height of 3±0.2 mm and diameter of 15±0.2 mm. The slices were put into the drying chamber after the target condition was steady for about 1 h. Then, the slices were placed on wire


513

meshes, which were weighed by the electronic bal-ance. The experiments were performed at air tempe-ratures 50, 60, 70 and 80 °C with a constant perpen-dicular air velocity of 1.2 m s-1. The mass of yam slices were recorded at first and about 17.5±0.5 g of yam samples were utilized in the each run. The weight of slices was recorded continuously at 3 s intervals during the drying process. For drawing the drying curve, the time for certain change of slice weight was obtained by manual statistics. The drying process was stopped until the weight of slices was invariable for more than 2 h. The final weight of dried slices was taken as the equilibrium moisture content (Me) that used to calculate the moisture ratio (MR). The yam slices were placed on the stainless steel wire mesh in an electric cooker and blanched by the saturated water steam at atmosphere. The blanching temperature was estimated at 98±2 °C and 100% relative humidity. All the yam slices were blanched at the same condition for 3 min prior to drying.

Mathematical modeling of drying curves

The moisture ratio (MR) can be calculated from the moisture content of drying sample at time t as

shown below:

*

*0

tX XMRX X

−=−

(1)

where Xt, X0 and X* are the moisture content at time t, the initial moisture content and the equilibrium moisture content, respectively; and the moisture con-tent X is expressed as:

d

d

tt

m mXm−= (2)

where mt and md are the mass of sample at time t and the final mass of dried samples, respectively.

The experimental convective drying data for Chinese yam were fitted to six thin-layer drying models. For the details of each model, readers can refer to the comprehensive review [3]. The empirical equations of each model are shown in Table 1.

The parameters of equations in Table 1 were estimated by using the nonlinear Levenberg-Marqu-ardt algorithm. The primary criterion for the selection of the best equation to describe drying curves was the coefficient of determination (R2). In addition, the chi

Figure 1. Schematic diagram of drying equipment.

Table 1. Mathematical models applied to fit the drying curves

Model No. Equation Model name Parameters Reference

1 MR = exp(-kt) Newton k [25] 2 MR = exp(-ktn) Page k, n [26] 3 MR = aexp(-kt) Henderson and Pabis a, k [27] 4 MR = 1+at+bt2 Wang and Singh a, b [28] 5 MR = aexp(-k t n) Modified page a, k, n [29] 6 MR = aexp(-kt)+c Logarithmic a, k, c [30]


514

square (χ2) and root mean square error (RMSE) were also used to determine the goodness of correlation. χ2 stands the mean square of the deviations between the predicted and experimental values of the equa-tion. It is known that the higher the values of R2, the lower were the values of χ2 and RMSE, and hence the better of model performance. These statistical para-meters are calculated by equations shown as below:

2,pre ,exp2 1

( )N

i iiMR MR

N nχ =

−=

− (3)

2,pre ,exp1

( )N

i iiMR MR

RMSEN

=−

= (4)

mean

mean

mean

2,exp ,exp2 1

2,exp ,exp1

2,pre ,exp1

2,exp ,exp1

( )

( )

( )

( )

Ni ii

Ni ii

Ni ii

Ni ii

MR MRR

MR MR

MR MR

MR MR

=

=

=

=

−= −

−

−−

−

(5)

where MRi,pre and MRi,exp stand for the ith predicted moisture ratio and the experimental moisture ratio, respectively; N is the number of observations, and n is the number of parameters in the drying equation.

Determination of effective moisture diffusivity

The effective moisture diffusivity coefficient is an important transport property in the drying of food mat-erials. It was calculated by fitting the experimental data to the Fick’s second law of diffusion equation:

effX XDt x x

∂ ∂ ∂ = ∂ ∂ ∂ (6)

With the assumption of uniform initial moisture distribution, negligible shrinkage and external resist-ance, constant diffusion coefficients and temperature, the solution of Eq. (6) for slab geometry is solved as follows [3,20]:

2 2eff

2 2 20

(2 1)8 1exp

(2 1) 4n

n D tMRn L

ππ

∞

=

− −= − (7)

where Deff is the effective moisture diffusivity (m2 s-1), t is the drying time (s), L is the half-thickness of samples (m). When for a long drying time, Eq. (7) can be simplified to the following equation:

2eff

2 28

exp4

D tMRL

ππ

−=

(8)

Plot ln(MR) against the time t gives the value of slope that contain the effective moisture diffusivity, Deff, as:

2

eff2Slope4

DL

π =

(9)

When given the value of the half-thickness of sample L, the Deff could be determined from Eq. (9).

Determination of activation energy

The activation energy for moisture diffusion, Ea, during the drying process can be related with the effective diffusion coefficient as following equation [19,20]:

( )a

eff 0 exp273.15

ED DR T

= − +

(10)

where D0 is the pre-exponential factor of the Arrhe-nius equation in m2 s-1, R is the universal gas cons-tant, and T is temperature in °C.

RESULTS AND DISCUSSIONS

Influence of drying air temperature

The change of moisture ratio, MR, with drying time at hot air temperatures of 50, 60, 70 and 80 °C for Chinese yam slices at thickness of 3 mm and air velocity of 1.2 m s-1 are shown in Figure 1. It is shown that the increase in hot air temperature leads to a decrease in the total drying time. It is well known that the higher temperature makes the relative humidity of air around sample slices become lower. As a result, the heat transfer and evaporation of water from the samples are greatly enhanced which then reduce the drying time. However, the drying rate increased as the temperature increased, but the increase became gradually smaller especially for the blanched yam slices as shown in Figure 2. Similar trends can also be found in several studies for different agricultural and food products [17,19-20].

On the other hand, although the increase of air temperatures can dramatically reduce the total drying time, it has disadvantageous effects on the total energy consumption and the quality of end products like the oxidation of phytochemicals and color deter-ioration [31]. For yam slices, it was found that the samples dried at 80 °C had the highest drying rate in all the temperatures concerned; however, the extent of surface hardening and shrinkage effect was inten-sified on the slice surface. This can be explained by the fact that the migration rate of moisture to the sur-face is lower than the moisture evaporation rate from


515

surface to air at that drying temperature. This allows the presence of phenomena such as hardening and shrinkage of yam slices. Moreover, high temperatures will also lead to color changes, which are not desir-able.

Influence of pretreatment on drying time

Pretreatment is an important parameter that affects the drying characteristics. As can be seen in Figure 1, the yam slices blanched prior to the hot air drying are found to shorten the drying time compared with the raw yam slices. For example, the total time required for the drying of raw yam slices to the MR of 10% at 60 °C is about 110 min, while for blanched yam slices 81 min are needed to reach this moisture content. Blanching pretreatment can shorten the dry-ing time with about 30% to reach the same moisture content at that condition. Similar trends are found at other drying temperatures. It is believed that the blanching pretreatment can loosen the cellular net-work and separate along the middle lamella in organic materials which then result in the softening of tissues [14-17]. Moreover, it was shown that the reducing cohesiveness of the matrix for food materials could improve the absorption capability of water, which led to better rehydration at their end use [32]. Further-more, blanching pretreatment can avoid enzymes to be active at least during the drying process [15]. These profiles have been regarded as beneficial effects of the blanching prior to hot air drying.

Fitting of drying curves

Six thin layer drying equations listed in Table 1 are used to correlate the experimental drying data of Chinese yam slices at 4 different drying temperatures (50, 60, 70 and 80 °C). These equations are fre-quently used in literatures for the description of drying

curves. The Levenberg-Marquardt algorithm is used to obtain the parameters of these six equations. The statistical parameters R2, χ2 and RMSE obtained for six equations are shown in Table 2. The best equa-tion that can describe the hot air drying characteristics of yam slices should with the highest R2 and lowest values of RMSE and χ2.

The results showed in Table 2 shows that the values of R2 are all greater than 0.94, indicating a good fitness. The values of R2, χ2, and RMSE for different equations for raw yam slices are range from 0.9487 to 0.9995, 0.000046 to 0.004033, and 0.006716 to 0.062729, respectively. Better results are obtained for blanched yam slices, the values of R2, χ2 and RMSE are range from 0.9754 to 0.9993, 0.006716 to 0.062729, and 0.006716 to 0.062729, respectively. Model 4 (Wang and Singh) gave the best results to fit the experimental data of yam slices for all tempera-tures, followed by model 5 (Modified page). The aver-age R2 of Wang and Singh equation for different tem-peratures is 0.9987 and 0.9989, respectively. Hence, the Wang and Singh model could be selected as the most suitable model to represent the thin-layer hot air drying behavior of the yam slices. For the conve-nience of calculation, the parameters of Wang and Singh equation are shown in Table 3 for raw and blanched yam slices. Actually, the Wang and Singh model use the polynomial equations to represent the logarithmic relation between MR and t. Many studies shows that the Wang and Singh model can be well used to represent the drying curves of different agri-cultural and food materials, such as green apples [33] and long grain paddy [34].

Effective moisture diffusivity

Table 4 shows the calculated effective moisture diffusivity, Deff, by Eq. (10) for the raw and blanched

Figure 2. Drying curves at different hot air temperatures for: a) raw yam slices and b) blanched Chinese yam slices.

S. FANG et al.: MATHEMATICAL MODELING AND EFFECT OF BLANCHING… CI&CEQ 21 (4) 511−518 (2015)

516

Table 2. The fitting models and statistical results for models at different temperatures

Table 3. Values of parameters of the Wang and Singh equation for raw and belched samples at different temperatures

T / °C Raw, a b×105 Blanched, a b×105

50 -0.007359 1.32 -0.009458 2.17

60 -0.011846 3.46 -0.015696 5.95

70 -0.014787 5.36 -0.023180 13.3

80 -0.020061 10.1 -0.027022 18.3

Table 4. The effective moisture diffusion coefficient (Deff) of raw and blanched yam at different temperatures

T / °C Deff×109 / m2 s–1

Raw Blanched

50 0.7295 1.3748

60 1.0126 2.3124

70 2.1314 3.5062

80 2.4087 3.8524

yam slices at different drying temperatures. The values of Deff varied in the range of 0.7295×10-9 to 2.4087×10-9 m2 s-1 for raw yam slices, while 1.3748×10-

9 to 3.8524×10-9 m2 s-1 for blanched samples. The results show that the values of Deff increased with the increase of drying temperature. For food materials, many studies have showed that the value of Deff are in a general range of 10-12 to 10-8 m2 s-1 [35]. Sobukola

et al. [23] obtained the values of Deff from 7.62×10-8 to 9.06×10-8 m2 s-1 for blanched yam slices (Dioscorea rotundata) under LTLT pretreatment. The values of Deff obtained in this study for Chinese yam (Dioscorea opposita) slices are similar to those for other food products, like 5.61×10-10 to 1.03×10-9 m2 s-1 for peach slices at 60-80 °C [20], 1.68×10-9 to 4.77×10-9 m2 s-1 for tomatoes at 40-80 °C [36], 2.74×10-9 to 4.64×10-9

Model No. T / °C Raw, RMSE χ2 R2 Blanched, RMSE χ2 R2

1 50 0.057294 0.003367 0.9841 0.062116 0.003900 0.9863

60 0.062729 0.003985 0.9871 0.059828 0.003778 0.9821

70 0.061973 0.004033 0.9865 0.062944 0.004255 0.9827

80 0.057206 0.003329 0.9883 0.056986 0.003518 0.9855

2 50 0.023414 0.000562 0.9880 0.017363 0.000305 0.9972

60 0.014301 0.000207 0.9982 0.024514 0.000634 0.9944

70 0.015781 0.000261 0.9978 0.022517 0.000545 0.9956

80 0.012782 0.000166 0.9985 0.019905 0.000429 0.9965

3 50 0.049036 0.002466 0.9487 0.049015 0.002428 0.9781

60 0.048641 0.002396 0.9790 0.051900 0.002843 0.9754

70 0.049362 0.002558 0.9789 0.053918 0.003123 0.9757

80 0.044447 0.002010 0.9826 0.049064 0.002608 0.9798

4 50 0.006716 0.000046 0.9995 0.013151 0.000175 0.9989

60 0.016413 0.000273 0.9984 0.008714 0.000080 0.9993

70 0.014555 0.000222 0.9988 0.015315 0.000252 0.9982

80 0.016872 0.000290 0.9979 0.010302 0.000115 0.9992

5 50 0.017493 0.000314 0.9969 0.013696 0.000190 0.9982

60 0.010864 0.000120 0.9989 0.019307 0.000393 0.9963

70 0.013701 0.000197 0.9983 0.019506 0.000409 0.9965

80 0.010041 0.000103 0.9989 0.016632 0.000300 0.9974

6 50 0.013664 0.000191 0.9980 0.016379 0.000271 0.9971

60 0.020035 0.000407 0.9958 0.015276 0.000246 0.9975

70 0.018209 0.000348 0.9966 0.025000 0.000671 0.9938

80 0.029604 0.000892 0.9908 0.022917 0.000569 0.9947


517

m2 s-1 for carrot pomace at 60-75 °C [37]. The differ-ences between these results can be explained by effect of material type, slice thickness, temperature and tissue characteristics. It can be found that the Deff values are larger than some root crops with more firm tissue characteristics, such as sweet potato slices at level of 9.32×10-11 to 1.75×10-10 m2 s-1 at 50-70 °C [11].

Activation energy

The activation energy of Chinese yam slices drying at temperature range 50-80 °C is obtained by the Arrhenius relationship as shown in the Eq. (10). The results and values are shown in the Eq. (11) and (12) for raw and blanched yam slices with R2 of 0.9407 and 0.9400, respectively:

3eff,raw

411493.223 10 exp

( 273.15)D

R T− −= × +

(11)

4eff,blanched

334993.879 10 exp

( 273.15)D

R T− −= × +

(12)

As shown in Figure 3, the values of activation energy are found to be 41.149 and 33.499 kJ mol-1 for raw and blanched yam slices, respectively. The values of activation energy of yam slice are in the range of 15-40 kJ mol-1 found for various food mat-erials [3]. As can be seen above, the obtained acti-vation energy are similar to those found by other authors for different agricultural and food products: 28.14 kJ mol-1 for tiger nuts [38]; 25.35 to 30.83 kJ mol-1 for blanched eggplant slices [39]; 38.78 kJ mol-1 in cape gooseberry [40]; 37.76 kJ mol-1 in red chilies drying [41].

Figure 3.The relationship of ln Deff and 1/R(T+273.15) for the

raw and blanched yam.

CONCLUSIONS

The effects of temperature on drying charac-teristics of raw and blanched Chinese yam slices were investigated. The results show that blanching pretreatment can reduce the total drying time com-pared to the raw samples. Six thin layer drying models were calculated and compared by their cap-ability in the correlation of drying curves at four tem-peratures. The Wang and Singh model gave best results with R2 of 0.9987 and RMSE of 0.0136 for raw yam slices, and R2 of 0.9989 and RMSE of 0.0119 for blanched samples. The effective moisture diffusivity coefficient, Deff, varied in the range of 0.7295×10-9 to 2.4087×10-9 m2 s-1 for raw slices, and 1.3748×10-9 to 3.8524×10-9 m2 s-1 for blanched samples. The acti-vation energy of yam slices drying were 41.149 and 33.499 kJ mol-1 for raw and blanched yam slices, respectively.

Acknowledgements

The authors acknowledge financial support from the National Natural Science Foundation of China (21006094).

REFERENCES

[1] L. Zhang, B. Bai, X.H. Liu, Y. Wang, M.J. Li, D.B. Zhao, Food Chem. 126 (2011) 203-206

[2] O.P. Sobukola, S.O. Awonorin, L.O. Sanni, F.O. Bamiro, J. Food Process Pres. 32 (2008) 343-360

[3] H. Kucuk, A. Midilli, A. Kilic, I. Dincer, Dry Technol. 32 (2014) 757-773

[4] A. Motevali, S. Minaei, M.H. Khoshtagaza, Energ. Conv. Manage. 52 (2011) 1192-1199

[5] H.W. Xiao, H. Lin, X. D. Yao, Z.L. Du, Z. Lou, Z.J. Gao, J. Food Eng. 5 (2009) 1-17

[6] H.W. Xiao, C. L. Law, D. W. Sun, Z.J. Gao, Dry Technol. 32 (2014) 418-427

[7] A.S. Zhu, K. Xia, Chem. Ind. Chem. Eng. Q. 19 (2013) 485-492

[8] S.Z. Fang, Z.F. Wang, X.S. Hu, Int. J. Food Sci. Tech. 44 (2009) 1818-1824

[9] H.W. Xiao, Z.J. Gao, H. Lin, W. X. Yang, J. Food Process Eng. 33 (2010) 899-918

[10] N.J. Singh, R.K. Pandey, Food Bioprod. Process 90 (2012) 317-322

[11] I. Doymaz, Heat Mass Transfer 47 (2011) 277-285

[12] R.P.P. Guine, S. Pinho, M.J. Barroca, Food Bioprod. Pro-cess 89 (2011) 422-428

[13] M. Igual, E. Garcia-Martinez, M.E. Martin-Esparza, N. Martinez-Navarrete, Food Res. Int. 47 (2012) 284-290

[14] I. Doymaz, Biosyst. Eng. 89 (2004) 281-287

[15] H.W. Xiao, J. W. Bai, D. W. Sun, Z.J. Gao, J. Food Eng. 132 (2014) 39-47


518

[16] J.W. Bai, D.W. Sun, H.W. Xiao, A.S. Mujumdar, Z.J. Gao, Innovat. Food Sci. Emerg. Technol. 20 (2013) 230-237

[17] J.W. Bai, Z.J. Gao, H.W. Xiao, X. T. Wang, Q. Zhang, Int. J. Food Sci. Tech. 48 (2013) 1135-1141

[18] M. Das Purkayastha, A. Nath, B.C. Deka, C.L. Mahanta, J. Food Sci. Tech. 50 (2013) 642-653

[19] I. Doymaz, O. Ozdemir, Int. J. Food Sci. Tech. 49 (2014) 558-564

[20] A.S. Zhu, X.Q. Shen, Int. J. Heat Mass Transfer 72 (2014) 345-351

[21] H.W. Xiao, X.D. Yao, H. Lin, W.X. Yang, J.S. Meng, Z.J. Gao, J. Food Process Eng. 35 (2012) 370-390

[22] Y.P. Lin, T.Y. Lee, J.H. Tsen, V.A.E. King, J. Food Eng. 79 (2007) 1295-1301

[23] O.P. Sobukola, O.U. Dairo, A.V. Odunewu, Int. J. Food Sci. Tech. 43 (2008) 1233-1238

[24] Y.C. Meng, J. Wang, S. Fang, J. Chen, Transac. CSAE 27 (2011) 387-392

[25] H. Kucuk, A. Midilli, A. Kilic, I. Dincer, Dry Technol. 32 (2014) 757-773

[26] V.T. Karathanos, V.G. Belesssiotis, J. Agr. Eng. Res. 74 (1999) 355-361

[27] M.S. Chhinnan, Transac. ASAE 27 (1984) 610-615

[28] M. Ozdemir, Y.O. Devres, J. Food Eng. 42 (1999) 225- –233

[29] O. Yaldız, C. Ertekin, Dry Technol. 19 (2001) 583-596

[30] I.T. Togrul, D. Pehlivan, J. Food Eng. 55 (2002) 209-216

[31] H.W. Xiao, J.W. Bai, L. Xie, D.W. Sun, Z.J. Gao, Food Bioprod. Process (2014), doi:10.1016/j.fbp.2014.08.008

[32] F. Kaymak-Ertekin, J. Food Sci. 67 (2002) 168-175

[33] I. Doymaz, Dry Technol. 27 (2009) 478-485

[34] M.R. Manikantan, P. Barnwal, R.K. Goyal, J. Food Sci. Tech. 51 (2014) 813-819

[35] E. Uribe, R. Lemus-Mondaca, A. Vega-Galvez, M. Zamo-rano, I. Quispe-Fuentes, A. Pasten, K. Di Scala, Food Chem. 147 (2014) 170-176

[36] T.S. Workneh, M.O. Oke, Int. J. Food Eng. 9 (2013) 75- –89

[37] N. Kumar, B.C. Sarkar, H.K. Sharma, J. Food Sci. Tech. 49 (2012) 33-41

[38] T.Y. Tunde-Akintunde, M.O. Oke, J. Food Process Pres. 36 (2012) 457-464

[39] I. Doymaz, E. Gol, J. Food Process Eng. 34 (2011) 1234- –1252

[40] A. Vega-Galvez, L. Puente-Diaz, R. Lemus-Mondaca, M. Miranda, M.J. Torres, J. Food Process Pres. 38 (2014) 728-736

[41] S. Kaleemullah, R. Kailappan, J. Food Eng. 76 (2006) 531-537.

SHENG FANG LI-PING WANG

TING WU

School of Food Science and Biotechnology Engineering, Zhejiang

Gongshang University, Hangzhou, China

NAUČNI RAD

MATEMATIČKO MODELOVANJE I EFEKAT PRETRETMANA BLAŠIRANJEM NA KINETIKU SUŠENJA KINESKOG JAMA (Dioscorea opposita)

U radu je analiziran uticaj pretretmana blaširanjem na kinetiku sušenja kriški kineskog jama (Dioscorea opposita). Eksperimenti sušenja su izvedeni na temperaturama od 60, 70, 80 i 90 °C. Analizirano je šest modela sušenja tankog sloja. Koeficijent determinacije (R2), hi-kvadrat test (χ2) i srednja kvadratna greška (RMSE) su korišćeni za analizu performansi modela za sirove i blanširane uzorke. Wang i Singh model daje najbolje rezul-tate sa R2 = 0,9987 i RMSE = 0,0136 za sirove uzorke, kao i R2 = 0,9989 i RMSE = 0,0119 za blanširane uzorke. Efektivni koeficijent difuzivnosti vlage je u opsegu od 0,7295×10-9 do 2,4087×10-9 m2 s-1 za sirove uzorke, a u opsegu od 1,3748×10-9 do 3,8524×10-9 m2 s-1 za blanširane uzorke. Energija aktivacije za sirove i blanširane kriške iznosi 41,149 i 33,499 kJ mol-1, redom. Rezultati pokazuju da pretretman blaširanjem može da smanji ukupno vreme sušenja i da poboljša efektivnu difuzivnosts vlage u odnosu na sirove uzorke.

Ključne reči: kineski jam, sušenje toplim vazduhom, kinetika, modelovanje, blan-širanje.




519

ZORANA ARSENIJEVIĆ1

TATJANA KALUĐEROVIĆ RADOIČIĆ2

MIHAL ĐURIŠ1

ŽELJKO GRBAVČIĆ2 1Institute of Chemistry, Technology

and Metallurgy - Department of Catalysis and Chemical

Engineering, University of Belgrade, Belgrade, Serbia 2Faculty of Technology and

Metallurgy, University of Belgrade, Belgrade, Serbia

SCIENTIFIC PAPER

UDC 66.096.5:536.2:51

DOI 10.2298/CICEQ141022008A

EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER IN THREE-PHASE FLUIDIZED BED COOLING COLUMN

Article Highlights • A three-phase fluidized bed was used to study the heat transfer characteristics of the

system • The overall heat transfer in this system was compared to the existing literature correl-

ations • The smallest error for the case of heat transfer correlation for fluidized beds was

obtained • A new correlation was proposed specifically for the three-phase countercurrent con-

tactor • Hydrodynamic parameters were calculated according to the available literature correl-

ations Abstract

A three-phase (gas-liquid-solid) fluidized bed was used to study the heat transfer characteristics of a system consisting of low-density (290 kg/m3) spherical particles (2 cm diameter) in a 0.25 m cylindrical column with counter-current flow of water and air. The experimental investigation and mathematical modeling of heat transfer between the hot air and the cooling water was car-ried out. The experiments were conducted for a variety of different fluid flow rates and inlet air temperatures, while the air flow rate was kept constant. Based on the obtained experimental results, a new correlation for heat transfer in a three-phase fluidized system was proposed. The mean percentage error between the experimental and the correlated values of the jHp obtained was 1.69%. The hydrodynamic parameters of the system were also calculated according to the available literature correlations.

Keywords: turbulent bed contactor, fluidization, heat transfer coefficient, hydrodynamics.

Three-phase fluidized bed systems provide very efficient contact between the present solid, liquid and gaseous phases. They can be applied in various physical, chemical and biochemical processes [1]. Three-phase fluidized bed systems offer considerable advantages over conventional packed-bed columns because they operate at high gas velocities, they have high mass-transfer rates and the mobility of the packing prevents plugging. This makes three-phase systems suitable for handling streams containing par-

Correspondence: Z. Arsenijević, Institute of Chemistry, Techno-logy and Metallurgy - Department of Catalysis and Chemical Engineering, University of Belgrade, Njegoševa 12, Belgrade, Serbia. E-mail: [email protected] Paper received: 22 October, 2014 Paper revised: 9 February, 2015 Paper accepted: 10 March, 2015

ticulate matter and precipitates. In addition, there is practically no channeling or bypassing. The high gas and liquid throughputs are made possible by bed expansion by which the flooding is avoided. Some of the disadvantages of three-phase systems include bed pulsations, back mixing in the liquid phase and mechanical erosion of the packing spheres. However, the characteristics of high capacity and high mass transfer and particulate removal rate enabled their successful industrial application. Hydrodynamic pro-perties of three-phase fluidized beds such as bed pressure drop, minimum fluidization velocity, liquid phase holdup, bubble properties, mixing character-istics and bed expansion are very important for anal-yzing their performance [2-16].

There are several types of three-phase fluidized bed systems [5]. The flow of the liquid and the gase-

Z. ARSENIJEVIĆ et al.: EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER… Chem. Ind. Chem. Eng. Q. 21 (4) 519−526 (2015)

520

ous phases in three-phase systems can be cocurrent or countercurrent. In the case of cocurrent flow of the liquid and the gas phase, the particles constituting the fluidized bed are usually of high density and of small particle diameter. In the case of countercurrent flow of the fluid phases, the fluidization phase can be either the gas or the liquid phase. Countercurrent fluidized beds in which the gaseous phase is used as fluidizing agent are characterized by the large spherical par-ticles of low density. These types of contactors are often referred to as turbulent bed contactors (TBC). In this work, a countercurrent system was investigated, in which the gaseous phase (air) flows upwards and is used as a fluidizing medium, while the liquid phase (water) flows downwards and is used as a cooling medium.

O'Neill et al. [3] classified the operating regimes of the three-phase turbulent bed contactors as type I and type II. In type I regime, fluidization begins before flooding in the column, while for type II regime, fluidiz-ation begins after flooding in the column. Vunjak-Novakovic et al. [4] developed a chart that can be used for the determination of the type of operating regime in TBC systems.

Packing density contributes significantly to the operating mode. Generally, the packing density of more than 300 kg/m3 is characteristic of the type II regime, while the packing density of less than 300 kg/m3 is characteristic of the type I regime. Increasing the flow rate of the liquid phase and the reduction of the particle diameter of the package also changes the mode from type I to type II. Therefore, unlike packed bed towers, TBC systems may operate in flooding conditions (type II) [5].

While the hydrodynamic parameters of the TBCs were investigated by many authors [2-16], to our knowledge there are no available models in the literature describing the heat transfer between the liquid and the gaseous phases in these types of con-tactors. The main aim of this work was the experi-mental investigation of the heat transfer between the cold water and the hot air in a countercurrent turbul-ent bed contactor. Based on the experimental find-ings, a model for the heat transfer coefficient between the liquid and gas phase in TBC was proposed. The hydrodynamic parameters of the system (the mini-mum fluidization gas velocity, pressure drop through the bed, liquid hold-up, and bed expansion) were calculated using the available literature models best suited for our experimental system [4]. The counter-current TBC contactor used in this work consisted of a bed of spherical particles and operated in type I regime.

EXPERIMENTAL SET-UP

The experiments were carried out in three-phase system with fluidized bed, which is used for cooling of the hot air, at different air and water flow rates. The experimental setup is shown in Figure 1. The mea-sured variables included the inlet and the outlet air temperatures (Tgi and Tge) as well as inlet and outlet water temperatures (TLi and TLe).

Figure 1. Experimental set-up of the three phase fluidized bed contactor (a - fan, b - butterfly valve for air flow rate regulation, c - throttle plates for air flow rate measurement, d - "U" mano-

meter, e - electric air heater, f - column, g - steel mesh 5mm×5 mm, h - bed of plastic spheres, i - water spraying

nozzles, j - drops separator, k - water flow rate control valve, L - rotameter; TIC - temperature indication and control,

TI - temperature indicator).

Experimental measurements were performed at constant inlet air volumetric flowrate (Vg) of 275 m3/h (at 20 °C) and constant inlet water temperature (TLi) of 16 °C. Particle Reynolds number (Rep) varies from 1795 to 1896 in the experiments because of the change of air velocity (ug), viscosity (μ) and density (ρg) with temperature. A total of 40 experimental points were obtained for different water flowrates and different inlet air temperatures. The parameters of the system and the conditions at which the measure-ments were made are shown in Table 1.

Based on the water mass flux as well as on the diameter and density of the spheres the operating regime was determined according to the diagram pro-posed by Vunjak-Novakovic et al. [4]. It is clear that


521

our experimental system is in the operational mode of type I.


Heat transfer coefficient

The purpose of the TBC used in this work was cooling of the hot air, which was introduced at the bottom of the column. Therefore, the objective was to achieve the gas outlet temperature as low as pos-sible, and to achieve the best possible heat transfer between the cold water and the hot air. The experi-mental data of the outlet gas temperature as a func-tion of liquid flow rate at constant air flow rate for three inlet air temperatures are shown in Figure 2. Figure 2 shows that with the increase in water flow rate, the outlet air temperature decreases, i.e. the cooling is improved, as expected.

The main objective of this study was the deve-lopment of the correlation for heat transfer between

the hot gas and the cooling water. If it is assumed that the entire amount of water is evenly distributed on the surface of the light solid spheres, the heat transfer actually occurs between the hot gas and the liquid film around the spheres. The overall heat transfer in this system includes the convective, conductive and the radiative heat transfer.

The radiative heat transfer coefficient is very small in temperature ranges lower than 600 °C [17], so it was neglected in this work, as the maximum tem-peratures in our system are in the range of 110 °C.

The conductive heat transfer between the hot air and the liquid film formed around the solid spheres was also neglected since the thickness of the liquid film around the particles was calculated to be between 0.012 and 0.023 mm (Figure 3). The conduction can be neglected through the hollow plastic sphere, since the air and plastic are substances with small thermal conductivity [18]. Only conduction can occur through the liquid film. The Biot number is defined as the ratio

Table 1. Basic parameters of the experimental system

Column diameter Dc 0.25 m

Column cross-sectional area Ac 0.04909 m2

Diameter of light spheres dp 0.02 m

Density of light spheres ρp 290 kg/m3

Density of water ρl 1000 kg/m3

Static bed height H0 0.25 m

Water inlet temperature TLi 16 ºC

Mass of the particles in the bed Mbed 1.779 kg

Mass of one particle (sphere) M1 1.215·10-3 kg

Number of particles Np 1465 pieces

The total external surface of the particles Ap 1.841 m2

Figure 2. The outlet air temperature as a function of water flow rate at constant air flow rate of Vg (20 ºC) = 275 m3/h (Gv = 331 kg/h) for

three inlet air temperatures.


522

of the convective to the conductive heat transfer, Bi = (hpL)/λwater, where the liquid film thickness (L = δ) was taken as a characteristic dimension. As the calculated values of the Bi numbers were much less than 1 (Bi << 1), it was concluded that there is negligible resistance to the heat transfer through the liquid film.

The liquid film thickness that is formed around the light spheres in the column was determined from Eq. (1) assuming that the entire amount of liquid present in the column is evenly distributed on the surface of the particles [19]:

( ) ( )p p3

l

mm %1000 1 1

2 100d h ρ

δρ

= + −

(1)

The obtained liquid film thickness is presented graphically as a function of the water flowrate for three inlet air temperatures: 108.5, 96 and 85 °C (Fig-ure 3). It can be seen that as the water flowrate increases, the thickness of the film also increases. On the other hand, the inlet air temperatures do not have a significant impact on the film thickness.

According to the above, it was assumed that the overall heat transfer coefficient K is approximately equal to the convective heat transfer coefficient and that all other mechanisms of heat transfer (conduc-tion, radiation) are neglected. Additionally, since the liquid film is very thin, it is appropriate to use the par-ticle diameter for all of the further calculations.

The heat transfer between the hot gas and the liquid film around the particles can be described according to the following equation:

p lmQ = KA tΔ (2)

where K ≈ hp, and:

gi Le ge Lilm

gi Le

ge Li

( ) ( )

ln

T T T Tt T T

T T

− − −Δ = −

−

(3)

The overall heat balance is shown by the following equation:

v pG gi ge L pL Le Li( ) ( )G C T T G C T T− = − (4)

where Gv and GL represent mass flow rates of air and water, CpL and CpG specific heat of air and water, Tgi and Tge inlet and outlet air temperature, TLi and TLe inlet and outlet water temperatures.

The amount of exchanged heat per unit time, Q, can also be determined from the total heat balance based on gas or on water. In this work, the balance is calculated on the basis of the gas phase, since the gas flowrate was kept constant:

v pG gi ge( )Q G C T T= − (5)

In the above heat balances (Eqs. (4) and (5)) heat losses were neglected.

According to Eqs. (2), (3) and (5), hp was cal-culated for each experimental run.

The obtained results are shown in Figure 4 as a function of Rep. It can be seen that with increasing Rep the heat transfer coefficient slightly decreases (except for the five points that do not follow the trend of other).

Since, to our knowledge, there are no literature correlations describing the heat transfer in turbulent bed contactors, the results obtained were compared to the correlations for heat transfer between the single sphere and the fluid flowing around it [20] as well as

Figure 3. Liquid film thickness in function of water flowrate.


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with the correlations for overall heat transfer in packed and fluidized beds [21]. In order to be able to compare the results with the mentioned correlations, Nup number was calculated according to the equation:

p pp

h dNu

λ= (6)

Ranz and Marshall [19] correlation for heat transfer from the flowing gas to the single sphere in the form of Nusselt number is:

= + 1/2 1/3p p2 0.6Nu Re Pr (7)

Kunii and Levenspiel [20] developed correl-ations for heat transfer in packed beds (Eq. (8)) and in fluidized beds (Eq. (9)) in the same form with different coefficients:

= + 1/3 1/2p p2 1.8Nu Pr Re (8)

ε = + − 1/21/3

p p2 1.5 (1 )Nu Pr Re (9)

The results of the comparison of our experimen-tal data with the mentioned correlations are shown in Figure 5. As can be seen from the Figure 5, our expe-rimental values of Nup lie mainly between the Nup numbers for the packed and fluidized bed systems, closer to the values of the fluidized bed. The mean percentage error of Nup in comparison with presented correlations is: for single spheres 49.2%, for packed bed 44.4%, and for fluidized bed 19.6%.

The smallest error obtained for the Nup number calculated according to the correlation for the fluidized bed was expected. However, an error of almost 20%

Figure 4. Dependence of heat transfer coefficient of Rep.

Figure 5. Comparison of the experimental values of Nup with literature correlations for single sphere heat transfer, packed and fluidized

bed heat transfer.


524

is significant and that is why a new correlation based on our experimental data was proposed.

In this work, a correlation for heat transfer coef-ficient calculation was developed in the form of jHp:

= pHp 1/3

p

Nuj

Re Pr (10)

The correlation is a function of gas and liquid flow rate and input and output gas temperatures (Eq. (11)):

1.78150.1129gi ge

Hpgi

0.0787T TLj

G T

− =

(11)

Comparison of experimental values of the jHp

and the jHp values obtained by Eq. (11) is presented in Figure 6. The mean percentage error between the experimental and the calculated values was 1.69%, which represents a very good agreement.

Hydrodynamic parameters of the system

There are a variety of correlations in the liter-ature for the calculation of basic hydrodynamic char-acteristics of three-phase fluidized bed contactors: liquid hold-up, pressure drop, minimum fluidization velocity and bed expansion [4-16]. However, the problem is that most of these correlations were derived for the specific test system and the range of the experimental data obtained in it. For the cal-

culation of the hydrodynamic characteristics of our experimental system, Vunjak-Novakovic et al. [4,6] correlations were chosen, since they were obtained in the systems that are the most similar to our system. The parameters of the system on which the experi-ments were carried out are given in Table 2. Table 3 shows the corresponding correlations of Vunjak-Novakovic et al. [4,6].

The hydrodynamic characteristics of three-phase fluidized bed contactors: liquid hold-up, pressure drop, minimum fluidization velocity and bed expansion were calculated by Vunjak-Novakovic et al. [4,6] correlations given in Table 3. The calculated values of hydrodynamic parameters in our TBC system are given in Table 4.

CONCLUSIONS

The experimentally investigated three-phase system consisted of a fluidized bed of light hollow spheres, with countercurrent flow of hot air and cool-ing water. The main objective of the study was the development of a correlation for heat transfer coef-ficient calculation. It was assumed that the total amount of liquid hold-up was evenly distributed on the surface of the solid spheres and that the heat transfer actually occurred between the hot gas and the liquid film around the spheres. The overall heat transfer in this system was compared to existing literature correl-ations for heat transfer between a single sphere and

Figure 6. Comparison between the experimental values of jHp and the values of jHp calculated from correlation (Eq. (11)).

Table 2. System parameters in Vunjak-Novakovic et al. [4,6] and in our work

Reference f H0 / cm ul / m s–1 ug / m s–1 Dc / cm dp / mm ρp / kg m–3

[4,6] 0.36-0.78 10-30 0-0.034 0-4 14-29 10-38 182-980

This work 0.7 25 1.73-1.84 0.001-0.002 25 20 290


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the fluid flowing around it, as well as with the correl-ations for overall heat transfer in packed and fluidized beds. The smallest error for the case of correlation for fluidized beds was obtained.

As the existing literature correlations for heat transfer did not have sufficient accuracy, a new cor-relation was proposed specifically for the three-phase countercurrent contactor, given in Eq. (11).

The basic hydrodynamic characteristics of the experimental system were also calculated according to the available literature correlations. The most appropriate correlations proposed by Vunjak-Nova-kovic et al. were chosen according to the parameters of the system.

Acknowledgement

Financial support of the Serbian Ministry of Education, Science and Technological Development (Project ON172022) is gratefully acknowledged.

Nomenclature

Ac – cross-sectional area of the column (m2) Ap – total particle outer surface area (m2) Bi – Biot number CpG – heat capacity of air (J/kg K) CpL – heat capacity of water (J/kg K) Dc – column diameter (m) dp – light particle diameter (m) f – fractional free area of support grid Frl –Froud number for liquid phase, ul/(gdp)

1/2 g – gravitational acceleration, 9.81 m2/s GL – water mass flowrate (kg/s) Gv – air mass flowrate (kg/s) H – height of expanded bed (m) H0 – static bed height (m)

h – liquid hold-up (%) hLo – operational liquid hold-up (m3/m3)

hp – convective heat transfer coefficient (W/(m2K)) jHp – heat transfer factor K – overall heat transfer coefficient (W/(m2K) ) L – water mass flux (kg/(m2 s)) M1 – weight of single sphere (kg) Mbed – bed weight (kg) Np – number of particles Nup – Nuselt number for particle Pr – Prantl number Q – exchanged heat per unit time (W) Rel – Reynolds number for water, (Dculρl)/μl Rep – Reynolds number for particle, (dpugρg)/μg Tge – outlet air temperature (°C) Tgi – inlet air temperature (°C) TLe – outlet water temperature (°C) TLi – inlet water temperature (°C) Vg (20°C) – volumetric air flowrate at 20 °C (m3/h) ug – superficial air velocity (m/s) ul – superficial water velocity (m/s) umf – minimum fluidization air velocity (m/s) Δp – pressure drop in the column (Pa) Δtlm – logaritmic temperature diffference

Greek symbols λ – air thermal conductivity (W/(m K)) λwater – water thermal conductivity (W/(m K)) ε0 – bed porosity εl,st – liguid hold-up in stationary regime (m3/m3) μ - air dynamic viscosity (Pa s) ρg – air density (kg/m3) ρl – water density (kg/m3) ρp – density of light plastic spheres (kg/m3) δ – liquid film thickness (mm)

Table 3. Used correlations for calculation of the basic hydrodynamic characteristics [4,6]

0.5670.858 0.139 0

l,st l lc

6.49 Re , Type I operationH

FrD

ε−

− =

[4] (12)

( )( ){ }20.50.5

1.2 3 0.568 0.719 4.788 10mF p 0 p g l p

g1 2.48 10 10 , , 0.064L gu kd d L k m

mε ρ ρ ρ

ρ−− − − ×

= − − + × = =

[6] (13)

( ){ }0 p 0 l 01 Lp h gHε ρ ρΔ = − + [6] (14)

( )

0.5670.568 0.7190

0 pc

0.2370 g

1 0.00248 0.02

, Type I operation1 0.62

H d LDH

H u

ε−

− − + + =

− [6]

(15)

Table 4. Calculated values of hydrodynamic parameters

εl,st / m3 m–3 Δp / Pa umF, avg / m s–1 (H/H0, avg) / m m–1

0.023–0.013 413.1-386.2 1.43 1.96


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Abbreviations TBC – Turbulent Bed Contactor

REFERENCES

[1] A. Pare, Master Thesis, National Institute of Technology, Rourkela, 2013

[2] A.W. Kielback, Chem. Eng. Prog. S. Ser. 57 (1959) 51-54

[3] B.K. O'Neill, D.J. Nicklin, N.J. Morgan, L.S. Leung., Can. J. Chem. Eng. 50 (1972) 595-601

[4] G.V. Vunjak-Novakovic, D.V. Vukovic, H. Littman, Ind. Eng. Chem. Res. 26 (1987) 958-966

[5] A. Haq, PhD Thesis, Pakistan Institute of Engineering and Applied Sciences, Islamabad, 2012

[6] G.V. Vunjak-Novakovic, D.V. Vukovic, H. Littman, Ind. Eng. Chem. Res. 26 (1987) 967-972

[7] A.E.R. Bruce, S.S.T. Pillutla, K. Kamatam, Can. J. Chem. Eng. 80 (2002) 337-345

[8] B.Z. Uysal, PhD Thesis, McGill University, Montreal, 1978

[9] M. Wozniak, Int. Chem. Eng. 17 (1977) 553–559

[10] J. Tichy, W.J.M. Douglas, Can. J. Chem. Eng. 50 (1972) 702-706

[11] J. Tichy, W. J.M. Douglas, Can. J. Chem. Eng. 51 (1973) 618-620

[12] J. Tichy, A. Wong, W.J. M. Douglas, Can. J. Chem. Eng. 50 (1972) 215-220

[13] M. Kito, Y. Kayama, K. Tsuchiya, T. Sakai, S. Sugiyama, Kagaku Kogaku Ronbunshu 2 (1976) 476-479

[14] A.H.J. Paterson, R. Clift, Can. J. Chem. Eng. 65 (1987) 10-17

[15] O.P. Rama, D.P. Rao, V. Subba Rao, Can. J. Chem. Eng. 61 (1983) 863-868

[16] A.E.R. Bruce, P.S.T. Sai, K. Krishnaiah, Chem. Eng. J. 99 (2004) 203-212

[17] A.P. Baskakov, N.F. Filippovskii, V.A. Munts, A.A. Ashikhmin, Inzhererno Fiz. Zh. 52 (1987) 788-793

[18] J.Z. Liang, F.H. Li, Polymer Testing 25 (2006) 527–531

[19] Z. Arsenijević, PhD Thesis, Faculty of Technology and Metallurgy, Belgrade, 2006

[20] W.E. Ranz , W.R. Marshall, Chem. Eng. Prog. 48 (1952) 141-146

[21] D. Kunii, O. Levenspiel, Fluidization Engineering, 2nd ed., Butterworth- Heinemann, Waltham, MA, 1991.

ZORANA ARSENIJEVIĆ1

TATJANA KALUĐEROVIĆ RADOIČIĆ2

MIHAL ĐURIŠ1

ŽELJKO GRBAVČIĆ2 1Institut za hemiju, tehnologiju i

metalurgiju – Centar za katalizu i hemijsko inženjerstvo, Univerzitet u

Beogradu, Beograd, Srbija 2Tehnološko–metalurški fakultet,

Univerzitet u Beogradu, Beograd, Srbija

NAUČNI RAD

EKSPERIMENTALNA ISPITIVANJA PRENOSA TOPLOTE U KOLONI ZA HLAĐENJE SA TROFAZNO FLUIDIZOVANIM SLOJEM

U okviru ovog rada je proučavan prenos toplote u trofaznom (gas–tečnost–čvrsto) fluidizo-vanom sloju. Eksperimentalna ispitivanja obavljena su u koloni prečnika 0.25 m sa flui-dizovanim slojem sferičnih čestica male gustine (290 kg/m3) prečnika 2 cm u suprotno-strujnom toku vode i vazduha. Izvršeno je eksperimentalno ispitivanje i matematičko modelovanje prenosa toplote između zagrejanog vazduha i vode za hlađenje. Ekspe-rimenti su izvršeni pri različitim protocima vode za hlađenje i različitim temperaturama zagrejanog vazduha, dok je protok vazduha održavan konstantnim. Na osnovu dobijenih eksperimentalnih rezultata predložena je nova korelacija za prenos toplote u trofaznom fluidizovanom sloju. Srednja procentualna greška između eksperimentalnih i korelisanih vrednosti faktora prenosa toplote, jHp, je iznosila 1,69%. Hidrodinamički parametri ispiti-vanog sistema su izračunati na osnovu raspoloživih literaturnih korelacija.

Ključne reči: turbulentni trofazni kontaktor, fluidizacija, koeficijent prenosa toplot-e, hidrodinamika.




527

VESNA S. CVETKOVIĆ1

LUKA J. BJELICA2

NATAŠA M. VUKIĆEVIĆ1

JOVAN N. JOVIĆEVIĆ1 1Institute of Chemistry, Technology

and Metallurgy, University of Belgrade, Belgrade, Serbia

2Faculty of Sciences and Mathematics, University of Novi

Sad, Novi Sad, Serbia

SCIENTIFIC PAPER

UDC 544.6:669.729:543.42

DOI 10.2298/CICEQ141205009C

ALLOY FORMATION BY Mg UNDER-POTENTIAL DEPOSITION ON Al FROM NITRATE MELTS

Article Highlights • Water removal from magnesium nitrate hexahydrate • Preparation of magnesium nitrate melts • Underpotential deposition of magnesium on aluminium substrate • Mg-Al surface alloy formation by UPD of magnesium Abstract

Magnesium was underpotentially deposited on aluminium electrodes from magnesium nitrate-ammonium nitrate melts at temperatures ranging from 390 to 500 K. The electrochemical techniques used were linear sweep voltammetry and potential step. Electrodes were studied by scanning electron microscopy (SEM), energy dispersive spectrometry (EDS), energy dispersive X-ray spec-troscopy (EDX) and X-ray diffraction (XRD). It was found that reduction pro-cesses of nitrate, nitrite and water (when present), in the underpotential range studied, took part simultaneously with magnesium underpotential deposition. Consequently, magnesium UPD reduction and stripping voltammetry peaks were not pronounced and well defined. Nevertheless, EDS, EDX and XRD measurements showed evidence of Mg2Al3, MgAl2 and Al12Mg17 alloys formed by underpotential deposition of magnesium onto aluminium substrate.

Keywords: magnesium/aluminium alloys, underpotential deposition, magnesium nitrate melts.

One of the ways to obtain a metal, and/or an alloy, under very controlled conditions is direct iso-thermal electrochemical deposition (electrodeposi-tion). The current density that sustains electroche-mical deposition of a metal, or an alloy, directly ref-lects the rate of the process [1].

However, metals like Li, Na, K, Al, Mg, Ti and W cannot be electrodeposited from water solutions, because hydrogen starts evolving on the working cathode before any of them start depositing. This pre-vents even the smallest amounts of the metal from remaining as a deposit on an electrode in a water solution without being dissolved. For electrodeposi-tion of Al, Mg and other metals, with very negative standard electrode potentials, melts based on chlo-

Correspondence: V.S. Cvetković, Institute of Chemistry, Tech-nology and Metallurgy, University of Belgrade, Njegoševa 12,11000 Belgrade. E-mail: [email protected] Paper received: 5 December, 2014 Paper revised: 26 February, 2015 Paper accepted: 20 March, 2015

ride salts at temperatures above 900 K are used. These are mainly inorganic or organic, chlorides or fluorides, salts that are combined with a cation of some alkaline/alkaline earth metal, or some organic cation or anion [1-3]. Ionic liquids (made of organic salts) became known relatively recently and proved to be suitable media for electrodeposition of metals and alloys at relatively low temperatures (from 273 to 373 K) [1,4].

To electrodeposit bulk of any metal, it is nec-essary to provide a working electrode with a potential that is more negative than the standard electrode potential of the depositing metal, this process is ref-erred to as overpotential deposition (OPD). It was also found that it is possible to co-deposit two or even three metals using overpotential deposition conditions and thus produce alloys on the surface of the working electrode.

Further detailed investigations of the processes that regulate electrodeposition of metals and alloys lead to the recognition of electrodeposition of metals on foreign substrates at potentials more positive than

V.S. CVETKOVIĆ et al.: ALLOY FORMATION BY Mg UNDERPOTENTIAL… Chem. Ind. Chem. Eng. Q. 21 (4) 527−536 (2015)

528

the equilibrium potential of the depositing metal (also referred to as underpotential deposition – UPD) [5]. In the last 40 years, UPD has been a subject of inten-sive experimental and theoretical interest. Most of the initial experimental work was done in aqueous elec-trolytes until the 1980s when the same phenomena was observed in deposition experiments of aluminium on gold, silver and copper from chloride melts at temperatures below 573 K [6-8].

It was soon found that a metal electrodeposited under UPD conditions from aqueous, non-aqueous solutions and melts at room temperatures onto a cathode of a different metal can diffuse into the sub-strate and generate alloys. Alloys obtained by electro-chemical deposition (OPD and UPD) can have dif-ferent chemical and phase structures than the alloys of the same composition obtained by metallurgical (thermal) methods [1,9].

Over the past ten years, the automotive industry has shown renewed interest in the applications of magnesium and its alloys, because magnesium with a density of 1.74 g/cm3 is 4.5 times lighter than steel and 1.6 times lighter than aluminium [10,11], while being able to achieve similar levels of ultimate strength in some alloys (200-250 MPa). As a result, magne-sium alloys offer a very high specific strength among conventional engineering alloys and have a wide application prospect in aerospace transportation, electronic engineering, as well as electrode compo-nents as chemical sources of electrical energy [12,13]. Currently, the most widely used magnesium alloys are based on the Mg-Al system [12]. Electrodepo-sition of magnesium and its alloys is of increasing importance in the development of rechargeable mag-nesium battery systems [14].

It is known that Mg cannot be deposited from solutions of simple Mg salts such as Mg(ClO4)4 in conventional organic solvents, for example, acetonit-rile, propylene carbonate or dimethylformamide. Most likely, this is due to the working electrode surface becoming covered by passivating surface films of very low ionic conductivity [14].

Available literature that references electrodepo-sition of magnesium from nitrate melts, and magne-sium underpotential deposition is rather limited, while that of alloy formation from nitrate melts is practically nonexistent. Physicochemical characteristics of nit-rate melts of alkaline and alkaline earth metals became a subject of interest in the second half of twentieth century [15-17] including their possible usage as elec-trolytes [18-20]. However, among a number of nitrate melts investigated electrochemically, neither mag-

nesium nitrate nor magnesium nitrate-ammonium nit-rate mixture melts were studied.

There are multiple reasons why these melts are not conducive to this work. Very pronounced oxidative characteristics of nitrates, great number of oxidation/ /reduction processes that can take place with cations and anions present in nitrates at the potentials more negative and more positive than the reversible poten-tial of magnesium [19,20], prevent realization of more experiments regarding metal electrodeposition from nitrate melts. Difficulties related to sustaining of the intended melt temperature variation below ±3 K arise from the large latent heats of the numerous nitrates, phase transformations in the temperature range from 373 to 500 K [15]. Also, it is impossible to remove water from magnesium nitrate hexahydrate by heat-ing, because it decomposes before it loses water and transforms into magnesium(II) oxide. The backbone of this octahedral complex is the magnesium cation [Mg(H2O)6]2+, which is very stable and cannot lose water thermally. As such, presence of water in mag-nesium melts cancels the advantages the melts have as compared to the magnesium aqueous solutions.

The aim of this work was to overcome the limit-ations of working on electrodeposition from nitrate melts, establish whether underpotential deposition of magnesium onto aluminium surface from magnesium nitrate melts occurred, and if it lead to magnesium/ aluminium alloy formation.

EXPERIMENTAL

Experiments were done under 99.99% Ar atmo-sphere in a three-neck (joints) electrochemical cell made of Pyrex glass placed in a heating mantle with temperature controlled (electronic thermostat) between 363 and 463 (±2 K). The central neck was closed with a PTFE plug carrying the working electrode (a 99.999% Al plate with active surface area of 0.4 cm2), the left neck with a PTFE plug holding an argon glass inlet-outlet and glass Luggin capillary with mag-nesium reference electrode (3 mm diameter 99.999% Mg wire), and the right neck with a Teflon plug hold-ing a magnesium anode (99.999% Mg) in the shape of a curved rectangular shovel (7.5 cm2 active surface area) and a tube of thin glass with a thermocouple. Argon and other possible gases coming out of the cell were captured/washed in two bottles (first with a slightly basic solution and second with a slightly acid solution). The entire cell setup was placed into a transparent plastic “glove box” in order to create a moisture free atmosphere around the cell.


529

The melts used in experiments were: non-aque-ous Mg(NO3)2, Mg(NO3)2⋅XH2O, eutectic mixture non- -aqueous Mg(NO3)2: NH4NO3 and eutectic mixture Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O.

The procedure for water removal from magne-sium nitrate hexahydrate consisted of two steps. The first step: the mixture of 5 g of magnesium nitrate hexahydrate and 15 cm3 of trimethyl orthoformate was brought to boiling and kept for 90 min under reflux at 343 K. In the first 20 min Mg(NO3)2⋅6H2O was completely dissolved in trimethyl orthoformate and after 45 min snow white crystals started appearing at the walls of the glass vessel. The second step: after 90 minutes of previous treatment, the mixture, now consisting of an ethyl ester of formic acid, methanol and crystals of non-aqueous magnesium nitrate, was subjected to vacuum distillation at 343 K. Upon rem-oval of the visible liquid, the remaining crystals were vacuum dried for additional 60 min. Non-aqueous magnesium nitrate was kept in a closed glass con-tainer in a desiccator furnished with plenty of silicagel. Ammonium nitrate hexahydrate was dried for 10 h at 378 K. Required amounts of magnesium nitrate alone, or mixtures with ammonium nitrate, were placed into the cell supplied with electrodes. Closed cell was then placed into the heating mantel, argon supply was turned on and the system was heated gradually to the wanted temperature.

The aluminium cathodes (99.999% Al) were mechanically polished by emery paper (FEPA P-4000) to a mirror finish and then etched in (50% HF + 15% H2O2) water solution for 30-60 s with intensive steering before being left in (NH4NO3 + 5% H2O2) sol-ution for 30-60 s. Finally, the electrodes were washed in deionised water, absolute ethyl alcohol, dried and mounted into the cell.

The magnesium anode and reference electrode (99.999% Mg) were mechanically polished by emery paper (FEPA P-4000) to a mirror finish and then etched in the solution, made of 78.2 cm3 conc. HNO3 + 23.4 cm3 conc. H2SO4 + 898.4 cm3 deionised water, in several 10 s intervals alternating with washing with deionised water. Finally, the electrodes were washed in deionised water, absolute ethyl alcohol, dried and mounted into the cell.

The electrochemical techniques used were: linear sweep voltammetry (LSV) and potential step. The potentials of working electrodes were measured in relation to the equilibrium potential of magnesium reference electrode in the melt used under the given conditions.

The cyclic voltammetry experiments included one or more cycles of the working electrode potential

cycling from a starting potential, ES (usually 50 to 100 mV more negative than the reversible potential of the Al working electrode) to a final potential, EF (which was positive to the reversible potential of Mg) and then back again to ES all at scan rates (between 5 and 100 mVs-1). The obtained results were recorded on an X-Y recorder.

The potential step method included change of the working electrode potential from an initial pot-ential, EI (50 to 100 mV more negative to aluminium equilibrium potential in the given melt) to a potential, EX (50 to 100 mV more positive to magnesium equi-librium potential in the given melt). EX potential was held constant for some time, whereupon the cathode was retrieved from the cell under potential in order to preserve deposited material or possible alloys formed during UPD of magnesium. The electrodes were suc-cessively washed with deionised water and absolute ethyl alcohol until visible remains of melt were rem-oved. The surfaces of the electrodes were analyzed by scanning electron microscopy (SEM - JEOL, model JSM-5800, Japan), energy dispersive spectrometry (EDS - Oxford INCA 3.2, U.K.), energy dispersive X-ray spectroscopy (EDX-maping - Oxford IncaEnergy EDX) and X- ray diffraction (XRD - Enraf Nonius pow-der diffractometer, Germany). IR analysis of the “anhydrous” magnesium nitrate was performed using Thermoscientific Nicolet 6700 (FT-IR) Smart Orbit Diamond (4000-200 cm-1).


It was important to make sure that the method of water removal from magnesium nitrate described above is effective. The mass difference between the magnesium nitrate hexahydrate entering the process of water removal and the magnesium nitrate leaving the said process was 39±3%. This would suggest that at least 92% of water had been removed. The dif-ference to 100% can be attributed to the residual methanol, methyl ester of formic acid or some of their derivatives because obtained Mg(NO3)2 crystals appeared to give off these chemicals immediately after drying. Obtained results strongly suggest that the process of water removing from magnesium nit-rate hexahydrate was successful. This conclusion is supported by the results obtained with IR and XRD analysis (Figures 1 and 2). The results of “anhydrous” magnesium nitrate IR analysis (Figure 1) show [21,22]: a) OH group at 3235 cm-1; b) CH groups at 2960 and 2850 cm-1; c) NO3 at 1344, 1128 and 1012 cm-1, possibly MgO group at 644 and 407 cm-1 and support the above conclusions.


530

Figure 2. XRD spectra of: a) non-aqueous eutectic mixture Mg(NO3)2 + NH4NO3, (*) Mg(NO3)2, (+) NH4NO3; b) eutectic

mixture Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O; (*) Mg(NO3)2⋅6H2O, (+) NH4NO3⋅XH2O [24,25].

In Figure 2a, XRD measurements do not show characteristic lines which would belong to the crystal structure of Mg(NO3)2⋅6H2O shown in Figure 2b. They show the lines, which with some reservations could be attributed to the crystals of “anhydrous” mag-nesium nitrate. The reservations are due to the fact

that the data on “anhydrous” magnesium nitrate in the available literature are very few and not fully reliable.

Contrary to work solutions where hydrogen ions are present and where hydrogen reference electrode can be universal, there is no universal reference electrode in experiments with melts. Therefore, in the systems where underpotential deposition is examined it is common practice to use the reversible potential of the depositing metal as a reference electrode potential with ascribed value of 0.000 V. In the nitrate melts used, for magnesium underpotential deposition on aluminium, a magnesium electrode was used as the reference electrode. Polarization measurements and cyclic voltammetry performed on the magnesium working electrode with magnesium reference and counter electrodes have shown that magnesium rev-ersible potential in the used magnesium nitrate melts, under temperatures ranging from 340 to 500 K, was stable [23]. Reversible potential of polycrystalline alu-minium in anhydrous Mg(NO3)2 melt at temperature interval between 360 and 400 K was 630±10 mV vs. Mg/Mg(II); in non-aqueous eutectic mixture Mg(NO3)2 + NH4NO3 at temperature between 390 and 500 K was 970±20 mV vs. Mg/Mg(II); in Mg(NO3)2⋅6H2O melt between 440 and 500 K was 260±30 mV vs. Mg/Mg(II) and in eutectic mixture Mg(NO3)2⋅6H2O + NH4NO3⋅xXH2O at temperature interval between 380 and 450 K was 1000±30 mV vs. Mg/Mg(II). With all other conditions being kept constant, the higher the temperature, the more positive aluminium reversible potential is. Addition of ammonium nitrate to magne-sium nitrate moved the aluminium reversible potential to more positive values as well.

Figure 1. IR spectrogram of Mg(NO3)2 crystals obtained after water removing process.


531

General characteristics of the voltammograms obtained in all melts used is that more than one red-uction peak was observed in the magnesium under-potential area, but with no oxidation counterparts. Typical example of the voltammograms obtained is presented in Figure 3. It can be seen that stripping peaks were not observed even when the cathodic end potential was pushed into the overpotential range. Sometimes reduction peaks were spread over a wider range of applied potentials without showing a steeper increase or decrease of current density values. Such structures of voltammogram peaks are characteristic for processes that start at close successive potentials and proceed simultaneously (often next process starts and increases rate while previous process dyes out with falling rate). Therefore, the obtained peaks represent a sum of all the rates of all the processes taking part at the certain potential.

Suggestions of possible processes that could produce reduction peaks in the magnesium UPD region investigated, apart from ones brought about by the magnesium underpotential deposition itself, can be found in rare published works [19,20]. The poten-tials of the proposed reactions measured relative to Na, K or Li cannot be directly used, but it can be assumed with enough certainty that the order of the potentials and their differences between these pro-cesses is preserved with respect to the magnesium reference potential. However, absolute values must be changed by the amounts that reflect differences in reference potentials between Na, K and Li in their nitrate melts and magnesium in used nitrate melts.

Reduction processes in the nitrate melts with water present, at the most anodic potentials, start with:

3 2 22NO 6H O 10e N 12OH− − −+ + + (1)

3 2 2NO H O 2e NO 2OH− − − −+ + + (2)

followed by the group of reactions with very close nitrate reduction potentials, in the melts with and without water present, which is reflected in wider cathodic voltammogram peaks:

23 2NO 5e 1/ 2N 3O− − −+ + (3)

23 2NO 2e NO O− − − −+ ↔ + (4)

23 2 22NO 2e 2NO O− − − −+ ↔ + (5)

23 22NO 8e N O 5O− − −+ ↔ + (6)

23NO 3e NO 2O− − −+ + (7)

which at their end decrease close to zero cathodic current densities. At potentials of –350 to –600 mV more negative to the previous peak, but still in the magnesium UPD region, next group of the nitrate reduction processes starts at mutually very close pot-entials:

23 2 22NO 2e 2NO O− − − −+ + (8)

23 2NO e NO O− − −+ + (9)

The absence of anodic (oxidation) counterparts to the cathodic peaks was a subject of a number of works [9,19,20,26-28]. These studies emphasize that changes of the aluminium electrode potential in nit-rate melts from anodic to cathodic values compared to magnesium reversible potential provoke passiv-ation of the working electrode which becomes parti-ally (or fully) covered with magnesium oxides layers. These layers do not dissolve when the potential is returned to the starting positive value.

In the UP region of the magnesium on alumi-nium cycle in nitrate melts used, the change of the electrode potential from positive values up to the

Figure 3. Linear sweep voltammograms of magnesium deposition onto aluminium electrode, υ = 30 mV s−1 from non-aqueous eutectic

mixture Mg(NO3)2 + NH4NO3 at T = 430 K, Ei = 0.700 V Ef = –0.550 V vs. Mg/Mg(II).


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magnesium reversible potential induces a number of reactions based on nitrogen, very reactive oxygen anion O2-, OH- and sometimes water. All produced gases were removed from the electrochemical cell by the argon stream, so when the electrode potential is reversed into positive direction, their possible theo-retical reverse oxidation reaction back to initial NO3

- or H2O could not be expected. As a result, no anodic voltammogram peaks could be recorded. Further-more, O2- produced in inner and outer parts of the electrochemical double layer very quickly engaged in reaction with present Mg2+ [9,19,20,26-28]:

2 2Mg O MgO+ −+ → (10)

the result being formation of insoluble magnesium oxides in the magnesium UPD region. The thermal decomposition constant [19,20] defines the stability of the possibly present magnesium hydroxide:

2 2Mg(OH) MgO H O+ (11)

However, examined anodic voltammogram peaks cannot be expected in the UP region.

In the melt made of eutectic mixture of mag-nesium nitrate and ammonium nitrate, at the tempe-ratures used, ammonium ion, resulting from NH4NO3 dissociation [19,20], form the compound (NH4)3Mg(NO3)5. In the melt this compound exists as a quasicrystalline structure made of NH4

+, Mg2+ and NO3

‒ [19,20]. The fact that reduction current densities in the magnesium nitrate melts increase with the inc-rease of the ammonium nitrate present, at the cons-tant temperature in the magnesium UP region inves-tigated, leads to the conclusion that NH4

+ reduction is

taking place:

4 3 22NH 2e 2NH H+ −+ → + (12)

However, this reaction is, under given condi-tions, irreversible and voltammograms could not show oxidation peaks when the electrode potential was rev-ersed in the positive direction.

It is logical to assume that the reduction peaks obtained by LSV measurements on the aluminium working electrode from magnesium nitrate and mag-nesium nitrate + ammonium nitrate melts in the mag-nesium underpotential region are sums of partial cur-rent densities for: Mg2+ underpotential reduction, nit-rate anion reduction and ammonium cation reduction. Being a sum, the recorded current densities suggest small magnesium underpotential deposition partial current densities. Such small current densities exhi-bited by the UPD voltammograms from similar melts [9,23,29,30] were characteristic of deposited metal monolayer diffusion into the substrate and forming alloys.

According to the Hume/Rothery rules [31], Mg and Al fulfil the required conditions to form alloys (solid solutions), including “the 15% rule”, because Mg and Al atomic radii differ only by 16.6%. EDS and XRD measurements obtained from the aluminium electrodes in used magnesium nitrate melts exposed to constant potentials in the magnesium underpot-ential region (50 to 150 mV vs. Mg/Mg(II)) supported the assumption.

An example of the indication that magnesium does underpotentially deposit on aluminium is exhi-bited in Figure 4 and represents SEM, EDS and EDX

Figure 4. a) SEM photograph for the surface of the Al electrode after 120 min holding at the potential of Ex = 60 mV vs. Mg/Mg(II) in

non-aqueous eutectic mixture Mg(NO3)2 + NH4NO3 at T = 450 K, mag. 2500x; b) EDS data for the sample in Figure 4a and EDX mapping; c) magnesium distribution image; d) oxygen distribution image; and e) aluminium distribution image

of the Al electrode surface.


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results obtained from the aluminium electrode held for two hours at magnesium underpotential of 60 mV vs. Mg/Mg(II) in a non-aqueous eutectic mixture Mg(NO3)2 + NH4NO3 at T = 450 K. A typical example of XRD analysis results on the aluminium sample exposed to underpotential of 60 mV vs. Mg/Mg(II) in the same melt and at T = 460 K for: a)1, b) 2 and c) 5 h are shown in Figures 5a-c, and strongly suggest that magnesium-aluminium alloys are being formed.

The results obtained by EDS, EDX (Table 1) and XRD (Table 2) analysis of Al substrates after being exposed to magnesium underpotential depo-sition to constant potential of 60 to 100 mV vs. Mg/Mg(II) for 120 min, from all used melts at the temperatures applied (under 500 K) seriously indicate that magnesium-aluminium alloys have been formed.

Table 1. Results of EDS quasi-quantitative analysis for the Al samples exposed to constant potential of 60 to 100 mV vs. Mg/Mg(II) for 120 min in used melts

Melt Al (at.%) Mg (at.%) O (mass%)

Mg(NO3)2⋅6H2O - - -

Mg(NO3)2 59.99 6.22 33.79

Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O 94.63 5.37 -

Mg(NO3)2 + NH4NO3 19.19 11.45 69.37

According to the Mg-Al phase diagrams [36,37], the equilibrium solid phases are: a) the fcc solid

solution with maximum solubility Mg in Al of at.18.9% at eutectic temperature of 723 K; b) the hcp solid solution with maximum solubility of Al in Mg of 11.8 at.% at eutectic temperature of 710 K; c) the β com-pound of approximate stoichiometry Al3Mg2, with complex fcc structure at low temperature, β trans-forms martensitically to another structure that may be a distortion of the β structure, but the equilibrium phase relations have not been investigated); d) the line compound R (or ε), of composition 42 at.% Mg; e) compound γ which at 723 K has a maximum com-position range of approximately 45-60 at.% Mg, but the ideal crystal structure has the stoichiometry Al12Mg17 at 58.6 at.% Mg. At the lower cooling rates, β, γ and γ' can be formed, while at higher cooling rates a new phase Φ was observed, found in a 30 at.% Mg alloy where a metastable solid solution and metastable phase appeared. Based on the structure, the new phase was identified as having stoichiometry Al2Mg.

All of the alloys described by the literature [36,37] have been recorded in magnesium under-potential deposition performed on aluminium in used nitrate melts but at temperatures that are several hundred K lower, Table 2. There is β compound (Al3Mg2) with complex fcc structure which is known to exist over a range of composition. This compound starts as a supersaturated Al solid solutions and

Figure 5. Diffraction patterns of aluminium sample after: a) 1, b) 2 and c) 5 h of magnesium underpotential deposition at Ex = 60 mV vs. Mg/Mg(II) in non-aqueous eutectic mixture Mg(NO3)2 + NH4NO3 at T = 460 K; a) (∙) (hcp) – Al0.9Mg3.1[32]; (*) (bcc) – Al12Mg17 [33];

(+) (hcp) – Mg2Al3 [34]; b) (+) (hcp) – Mg2Al3 [34]; (*) (bcc) – Al12Mg17 [33]; c) (+) (hcp) – Mg2Al3 [34]; (*) (bcc) – Al12Mg17 [33]; (∙) – (rhombohedral) MgO4 [35].


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undergoes a phase transformation through continued decomposition by formation of a nonequilibrium phase β' and solid solution with less Mg content than equilibrium, and ends up in the formation of equi-librium β phase. The metastable solid solution with relatively high Mg content (up to 30 at.%) with approx-imate stoichiometry Al2Mg was also recorded. The apparent existence of Al12Mg17 (at 58.6 at.% Mg) is a rather convincing argument in support of very suc-cessful interdiffusion of Mg and Al during magnesium underpotential deposition onto aluminium performed here at temperatures ranging from 390 to 500 K.

Table 2. Alloys identified by XRD analysis on Al substrates exposed to constant potential of 60 to 100 mV vs. Mg/Mg(II) (magnesium UPD) for 120 min in used melts

Melt Alloy 1 Alloy 2

Mg(NO3)2⋅6H2O bcc - Al12Mg17

Mg(NO3)2 bcc - Al12Mg17 fcc - Al3Mg2

Mg(NO3)2⋅6H2O + NH4NO3⋅xH2O fcc - Al2Mg hcp - Mg2Al3

Mg(NO3)2 + NH4NO3 bcc - Al12Mg17 hcp - Mg2Al3

Which of the magnesium adatoms formed by underpotential deposition on aluminium surface par-ticipate in oxide formation and which ones diffuse into substrate and contribute to alloy formation could not be concluded by linear sweep voltammetry, EDS or XRD results. LSV results indicated, EDS and XRD results confirmed, formation of both the magnesium oxide and the magnesium-aluminium alloy at the sur-face of the aluminium electrode in nitrate melts used. Eqs. (3)–(9) describe sources of oxygen needed for the process shown in Eq. (10) in the absence of water and Eq. (11) magnesium oxide formation in the pre-sence of water in the melt. In addition, some novel results [26-28] suggest that every amount of reactive magnesium on the electrode surface in the presence of O2- and OH- very quickly becomes MgO. Therefore, the surface of the aluminium working electrode becomes partially covered with MgOx even in the first linear change of the potential from anodic end to cathodic end of the magnesium underpotential range. This, however, did not preclude enough of magne-sium adatoms from participating in magnesium-alu-minium alloys formation by interdiffusion. Part of the magnesium ions in magnesium (II) oxide probably diffuse through the oxide layer to the aluminium sur-face where they become discharged into magnesium adatoms which are then participating in the interdif-fusion processes. Fast and unavoidable formation of insoluble MgO in the magnesium underpotential deposition range on aluminium from used nitrate melts explains quasi-passivation of the working elec-

trode and the lack of anodic current peaks on the vol-tammograms recorded.

CONCLUSIONS

The value for the half of work function difference in the case of Al and Mg is 0.20 to 0.30 eV and magnesium should show an underpotential deposition on aluminium at potentials close to 0.100 V vs. Mg/Mg(II). This work has confirmed UPD of Mg on Al substrate from nitrate melts used at potentials very close to 100 mV vs. Mg/Mg(II).

However, this rule does not predict whether there are going to be alloys formed between the sub-strate and underpotentially deposited metal. And yet, the most pronounced effects of the established mag-nesium underpotential deposition from magnesium nitrate melts used were three alloys formed with alu-minium substrate: Al12Mg17, Mg2Al3 and metastable solid solution Al2Mg. All the alloys obtained were formed at the temperatures several hundred Kelvin degrees lower than the temperatures which are, according to the relevant existing binary phase dia-grams, needed for their formation thermally.

It was established that underpotential deposition of the metals unsuitable for electrodeposition from aqueous electrolytes, like magnesium, can be per-formed even from low temperature nitrate melts and that it can lead to the formation of alloys in a very controlled way under more technologically suitable conditions than most of the known ones.

Acknowledgement

This work was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Grant ON 172060).

REFERENCES

[1] D.M. Kolb, in Advances in electrochemical science and engineering, Vol. 7, R.C. Alkire, D.M. Kolb, Eds., Wiley- -VCH, Weinheim, 2001, p. 150

[2] A.M. Martinez, G.M. Haarberg, B. Borresen, Y. Cas-trillejo, R. Tunold, J. Appl. Electrochem. 34 (2004) 1271- –1278

[3] Z. Lu, A. Schechter, M. Moshkovich, D. Aurbach, J. Elec-troanal. Chem. 466 (1999) 203-208

[4] G. Mamantov, C.L. Hussey, R. Marassi, in: Techniques for characterisation of electrodes and electrochemical processes, R. Varma, J.R. Selamn, Eds., John Wiley and Sons, New York, 1991, p. 471

[5] D.M., Kolb, M. Przasnyski, H. Gerischer, J. Electroanal. Chem. 54 (1974) 25-38

[6] B.S. Radović, R.A.H. Edwards, J.N. Jovićević, J. Electro-anal. Chem. 428 (1997) 113-121


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[7] B.S. Radović, V.S. Cvetković, R.A.H. Edwards, J.N. Jovi-ćević, Kovove Mater. 48 (2010) 159-171

[8] B.S. Radović, V.S. Cvetković, R.A.H. Edwards, J.N. Jovi-ćević, Kovove Mater. 48 (2010) 55-71

[9] G.L. Stafford, C.L. Hussey, In Advances in Electroche-mical Science and Engineering, Vol. 7, R.C. Alkire, D.M.Kolb, Eds., Wiley-VCH, Verlag GmbH, Weinhaim, 2002, p. 275

[10] L.L. Rokhlin, In Advances in Metallic alloys, Vol. 3, J.N. Fridlyander, D.G. Eskin, Eds., Taylor& Francis, New York, 2003, p. 1

[11] P.A. Friedman, W.B. Copple, JMEP 13 (2004) 335-347

[12] Z.H. Ye, X.Y. Liu, J. Mater. Sci. 39 (2004) 6153-6171

[13] D. Eliezer, E. Aghion, F. H. Froes, Adv. Perform. Mater. 5 (1998) 201-212

[14] Y. Viestfrid, M.D. Levi, Y. Gofer, D. Aurbach, J. Electro-anal. Chem. 576 (2005) 183-195

[15] K.V. Ramana, R.C. Sharma, H.C. Gaur, J. Chem. Eng. Data 31 (1986) 288-291



[18] K. Bhatia, R.C. Sharma, H.C. Gaur, Electrochim. Acta 23 (1978) 1367-1369

[19] D.A. Tkalenko, Elektrokhimiya nitratnykh rasplavov, Naukova Dumka, Kiev, 1983

[20] D.A. Tkalenko, Makrokinetika katodnykh protsessov v gidroksidnykh i nitratnykh rasplavakh, Naukova Dumka, Kiev, 1993

[21] A.G. Adebayo, Y. Liang, R.C. Miranda, S. Scandolo, J. Chem. Phys. 131 (2009) 014506

[22] A.M. Hofmeister, E. Leppel, K.A. Speck, Mon. Not. R. Astron. Soc. 345 (2003) 16-38

[23] V.S. Cvetković, Underpotential Electrochemical deposition of magnesium from nitrate melts“, Zadužbina Andrejević – PMF K. Mitrovica, Belgrade, 2012 (in Serbian)

[24] D. Weigel, B. Imelik, M. Prettre, Bull. Soc. Chim. Fr. (1964) 2600-2602

[25] R.J.Cernik, R. Delhez, E.J. Mittemeijer, Mater. Sci. Forum 359 (1996) 228-231

[26] N. Amir, O.V. Chusid, D.G. Aurbach, J. Power Sources 174 (2007) 1234-1240

[27] A.M. Martinez, B. Børrensen, G.M. Haarberg, Y. Cat-rillejo, R. Tunold, J. Electrochem. Soc. 151 (2004) C508

[28] A. Brenner, in Advances in electrochemistry and electro-chemical engineering, C.W. Tobias, Ed., Interscience, New York, 1967, p.25

[29] B.S. Radović, V.S. Cvetković, R.A.H. Edwards, J.N. Jovi-ćević, Int. J. Mater Res. 102 (2011) 59-68

[30] N. Jovićević, V.S. Cvetković, Ž.J. Kamberović, J.N. Jovi-ćević, Metall. Mater. Trans., B 44 (2013) 106-114

[31] W. Hume-Rothery, R.E. Smallman, C.W. Haworth, The structure of metals and alloys, 5th ed., The Institute of metals, London, 1969

[32] H.L. Luo, C.C. Chao, P. Duwez, Trans. Met. Soc. AIME 230 (1964) 1488-1489

[33] C. Suryanarayana, Z. Metallkd. 69 (1978) 155-156

[34] B. Ribar, F. Gabela, R. Herak, B. Prelesnik, Z. Kristallogr. Kristallgeom. Kristalphys. Kristallchem. 137 (1973) 290- –294

[35] V.M. Bakulina, S.A. Tokareva, E.I. Latysheva, J. Struct. Chem. 11 (1970) 150

[36] M. Hansen, K. Anderko, Constitution of binary alloys, McGraw-Hill, New York, 1958

[37] T.B. Massalski, Binary alloy phase diagrams, ASM, Metals Park, OH, 1990.


536

VESNA S. CVETKOVIĆ1

LUKA J. BJELICA2

NATAŠA M. VUKIĆEVIĆ1

JOVAN N. JOVIĆEVIĆ1 1Institut za hemiju, tehnologiju i

metalurgiju, Centar za elektrohemiju, Univerzitet u Beogradu, Beograd,

Srbija 2Prirodno-matematički fakultet,

Univerzitet u Novom Sadu, Novi Sad, Srbija

NAUČNI RAD

FORMIRANJE LEGURA ELEKTROTALOŽENJEM Mg PRI POTPOTENCIJALIMA NA Al IZ RASTOPA NITRATA

Ispitivano je elektrotaloženje magnezijuma pri potpotencijalima (underpotential deposition - UPD) na elektrodi od aluminijuma iz rastopa smeše magnezijum nitrata i amonijum nitrata na temperaturama od 390 do 500 K. Elektrohemijske tehnike koje su korišćene bile su ciklička voltametrija i metoda potenciostatskog pulsa. Nakon elektrotaloženja magnezijuma pri potpotencijalima aluminijumske elektrode ispitivane su skenirajućom elektronskom mikroskopijom (SEM), energetsko disperzivnom spektroskopijom (EDS), energetsko disperzivnom spektroskopijom X-zraka (EDX) i metodom difrakcije X-zraka. Utvrđeno je da reakcije redukcije nitratnih i nitritnih jona i vode (kada je prisutna), koje se odigravaju u istom i širem području potpotencijala magnezijuma učestvuju istovremeno sa reakcijama elektrolitičkog taloženja magnezijuma u datom rastopu i deformišu i/ili prekrivaju reduk-cione struje elektrotaloženja magnezijuma. EDS, EDX i XRD merenja su pokazala da dolazi do formiranja Mg2Al3, MgAl2 and Al12Mg17 legura kao posledice elektrotaloženja magnezijuma pri potpotencijalima na elektrodama od Al u ispitivanim rastopima.

Ključne reči: magnezijum/aluminijum legure, elektrotaloženje pri potpotencija-lima, rastopi magnezijum-nitrata.




537

RAJAMOHAN NATARAJAN1

JAMILA AL-SINANI1

SARAVANAN VISWANATHAN2

1Faculty of engineering, Sohar University, Sohar, Oman

2Department of Chemical Engineering, Annamalai University,

India

SCIENTIFIC PAPER

UDC 547.532:66:544

DOI 10.2298/CICEQ141022010N

PERFORMANCE EVALUATION AND KINETIC STUDIES ON REMOVAL OF BENZENE IN UP-FLOW TREE BARK BASED BIOFILTER

Article Highlights • The removal of benzene at different in loading rates were studied in a biofilter employing

a novel biofilter media • The performance was evaluated in terms of removal efficiency and elimination cap-

acity • The effect of flow rates of influent pollutant and biofilter bed height was studied • Carbon dioxide gas production profile was recorded and related with elimination cap-

acity • Kinetic modeling was performed and the constants were estimated Abstract

This study aims to evaluate the feasibility of Phoenix dactylifera tree barks as the novel filter medium in an upflow biofilter employing mixed culture to deg-rade benzene. The experiments were conducted at different benzene concen-trations (1.5-6.0 g m-3) and EBRT (1.2-4.7 min). The elimination capacity was found to vary linearly with inlet loading rate in the range of 0–306 g m–3 h–1. Removal efficiency of 99% was achieved when the benzene concentration was 1.5 g m-3 and decreased with increase in benzene concentration. Lower flow rates resulted in higher benzene removal efficiency. The concentration profile was observed at different heights of filter media. Temperature increase during biofiltration experiments confirmed the exothermic nature of biofiltration. The carbon dioxide production rate was related to elimination capacity by the equation CPR = 1.76EC + 18. A Michaelis-Menten type model was applied and the kinetic constants, maximum elimination capacity, ECmax’ and saturation constant, Ks were found to be 217.4 g m–3h–1 and 3.54 g m–3, respectively.

Keywords: kinetics, benzene, pollution.

Volatile organic compounds (VOCs) are con-sidered to be a potential group of contaminants for atmospheric air pollution caused through ozone layer depletion and greenhouse effect. Benzene, along with toluene, ethyl benzene and xylene, forms a group of VOCs called as BTEX compounds and are reported to contribute 59 mass% of gasoline pollutants [1,2]. Benzene is a potential carcinogen while the others are mutagenic. These pollutants are listed in the Eur-opean Pollutant Release and Transfer Register [3]. Due to the harmful nature of benzene, Environmental Protection Agency has set a target to lower the ben-

Correspondence: N. Rajamohan, Faculty of Engineering, Sohar University, Sohar, Oman. E-mail: [email protected] Paper received: 22 October, 2014 Paper revised: 9 March, 2015 Paper accepted: 31 March, 2015

zene concentration to 0.62% by 2011 [4]. Long term exposure of benzene leads to leukemia, excessive bleeding, anemia and immune system disorders [5,6]. Major sources of VOCs occur through storage tank losses, process vessel vents, refining operations, automotive emissions, heat exchangers and leaks from piping network and equipment [7]. In addition, VOCs are released by several industries including chemical industries, foundries, printing and coating industries, electronics and paint manufacturing indus-ries. Various technologies available for VOCs control include absorption, incineration, ozonation, mem-brane separation, etc. However, these methods suffer from demerits like high operating costs, lower removal efficiency and secondary pollution problems [8]. In this background, biotechnological processes evolved and gained popularity due to their simplicity and cost-

R. NATARAJAN et al.: PERFORMANCE EVALUATION AND KINETIC STUDIES… Chem. Ind. Chem. Eng. Q. 21 (4) 537−545 (2015)

538

effectiveness. Different bioreactor configurations, namely biofilters, bio trickling filters, bio scrubbers and suspended growth bioreactors are available for VOC treatment [9]. Biofiltration is one of the biotech-nological processes which involve the use of packing media over which pollutant decomposing microorg-anisms are immobilized as a biofilm. The pollutant laden air is passed through the biofilter column and transferred from the air stream to the biofilm due to the difference in concentrations [10]. A series of pro-cesses like absorption, diffusion and degradation are involved in this process [11] and involves physical, chemical and biological interactions [12]. In all ins-tances, the microorganisms are reported to convert the organics to carbon dioxide and water vapor. The food source is provided by the organic compound which helps in multiplication or activity of microorg-anisms [13]. Various factors like particle size and surface area of packing media, pH, carbon source, temperature and solubility of target pollutant are reported to affect the efficiency of biofilters [14,15]. Biofilter operations have been reported under unsteady-state, transient, short term and long term shock loads, shut down and starvation conditions [16,17]. Different packing media like compost and pumice [18], press mud [19] and corn stacks [20] have been investigated in various biofiltration studies. Biofiltration of benzene was reported using Stenotro-phomonas maltophilia 3c in a polyurethane based biofilter [21]. Biofiltration of benzene in a compost based biofilter was investigated in the concentration range up to 1.7 g/m3 and removal efficiency of 90% was reported [22]. BTEX degradation was evaluated as separate substrates and in mixtures, in liquid culture, and in packed biofilters with the filamentous fungus Paecilomyces variotii CBS115145 and a ben-zene elimination capacity of 10 g C m-3 h-1, was reported [23]. The maximum elimination capacities of benzene obtained, at an inlet load of 6.12 g m-3 h-1, were 3.50 and 3.80 g m-3 h-1 with raw and ground sugarcane bagasse based biofilter, respectively [24]. Studies on biofiltration of benzene at very high con-centrations were few and the choice of date palm tree bark as a filter media was not investigated earlier. In this experimental work, the feasibility of a novel bio-filter media for biofiltration of benzene under meso-philic conditions was studied. The biofilter perfor-mance was evaluated in terms of removal efficiency and elimination capacity. The influence of inlet load-ing and flow rate of the pollutant on the elimination capacity was investigated. In addition, axial concen-tration profile and biomass growth variations are

monitored. Kinetic modeling was performed and the constants were evaluated.


Biofilter media

The biofilter media used in this study was date palm tree barks. Date palm tree, Phoenix dactylifera, belongs to the Palmae (Arecaceae) family and is a native to Middle East countries where it is found in large number and used as a staple food in Oman. The tree barks were cut into pieces and screened for sizes lesser than the diameter of the column by eight times in order to avoid preferential flow on the side of the column walls [25]. Physicochemical characterization studies were performed to verify the chemical resist-ance of the filter media. The chemical resistance of novel packing medium was tested by placing it in glass beakers containing pure benzene, tap water, acidic (pH 4.91) and basic (pH 9.23) solutions for 30 days. The filter media were then removed from the solution, rinsed repeatedly with deionized water, dried in an oven at 60 °C for 24 h, cooled in a desiccator, and then reweighed. A slight change in color was observed and the weight losses of 2.0 and 2.6% were recorded with the samples placed in acidic and basic solutions respectively. The choice of this filter media was justified by its extensive availability and environ-mentally friendly disposability due to the natural bio-degradaing ability in the longer duration.

Inoculum

The biofilter media was sterilized with an auto-clave four times at 120 °C for 60 min and mixed with 40 mL of an activated sludge (1.5% w/V) collected from a municipal wastewater treatment plant in a 5.0 L tank. After standing overnight, the biofilter was loaded with the filter media in different sections. The concentrated sludge was cultured in an aerated batch reactor and diluted in 1 L of nutrient solution con-taining the following composition: K2HPO4 – 3.84 g L-1, KH2PO4 – 1.94 g L-1and NH4Cl – 3.00 g L-1, at pH 6.9. The packing media was mixed with the sludge in the biofilter column and drained after 24 h and this pro-cedure was repeated several times until visible biofilm formation was noticed on the biofilter media.

Experimental studies

The biofilter reactor set up consists of an acrylic column with an inside diameter of 5 cm and column height of 100 cm. The biofilter column was equipped with two sets of sampling ports located at 0 cm (inlet), 25 cm (section-1), 50 cm (section-2), 75 cm (section- -3) and 100 cm (exit), for treated gas sampling and


539

temperature measurements along the height of the biofilter. The treated gas was collected at the reactor headspace and nutrient feed addition was performed at the top of the column while a 10 cm bottom space was utilized for leachate collection was provided. Fig-ure 1 shows the biofilter setup with its components. The biofilter column is equipped with a carbon dioxide gas sensor (Extox, Germany) connected at the exit. The synthetic benzene polluted air stream was gener-ated by injecting a low flow compressed air stream into the benzene tank. The air stream loaded with benzene was mixed with the humidified pure air stream in the mixing chamber in order to attain the desired inlet concentration and fed into the biofilter reactor in an up flow mode. The air flow rates are regulated in the low (0-0.3 L min-1) and high (0-10.0 L min-1) flow rate range using rotameter. All the gas flow rates are manipulated using brass control valves. The operating parameters are varied in the ranges: inlet benzene concentration 1.5-6.0 g m-3 and flow rate 0.25-1.0 m3 h-1 and the samples were collected at periodic intervals for analysis of residual benzene. The nutrient solution, basal salts medium, with the fol-lowing composition: K2HPO4 – 0.91 g; Na2HPO4⋅2H2O – 2.39 g; (NH4)2SO4 – 1.97 g; FeSO4⋅2H2O – 0.2 g; MgSO4⋅7H2O – 2.0 g; MnSO4⋅7H2O – 0.88 g; Na2MoO4⋅2H2O – 1.0 mg; CaCl2 – 3.0 mg; ZnSO4⋅7H2O – 0.04 g and CoCl2⋅6H2O – 0.04 mg per litre of water was sprayed twice a day through the nutrient distri-bution system equipped with a peristaltic pump and spray nozzle. The nutrient solution along with the humidified air helps in maintaining the required rel-ative humidity in the biofilter.

Analytical methods

Inlet and exit benzene concentrations in gas samples were measured by gas chromatograph (Per-

kin-Elmer, USA) equipped with a FID and a capillary column, operated in off-line mode. The temperature conditions were 160 °C for injector and 280 °C for detector. The oven temperature was set at 60 °C for the first 5 min and increased at a rate of 15 °C per min to reach 180 °C and held at 4 min. Helium was used as a carrier gas at a flow rate of 2 ml min-1. The temperature of the filter bed was measured using temperature sensors connected to a data logger. The head space gas was analysed for carbon dioxide con-centration using online gas analyzer (Extox, Ger-many).

Performance evaluation

The performance of the biofilter was measured in terms of the removal efficiency (%RE), elimination capacity (EC), g m–3 h–1, and carbon dioxide pro-duction rate (CPR), g m–3 h–1. These parameters are defined as given below:

0

0

% 100 tC CREC−= (1)

-3 -10( ) (g m h )tQ C CEC

V−= (2)

2 2CO out CO ,in -3 -1( ) (g m h )

Q C CCPR

V−

= (3)

The Empty Bed Residence Time (EBRT) is defined as:

VEBRTQ

= (h) (4)

The inlet loading rate (ILR) is defined as:

-3 -10 (g m h )QCILRV

= (5)

Figure 1. Biofiltration experimental setup.


540

where C0 and Ct represent the inlet and exit concentrations of benzene (g m-3), Q is the flow rate of the benzene (m3.h-1),V is the volume of the biofilter (m3), CCO2out and CCO2,in represent exit and inlet con-centrations of carbon dioxide (g m-3).


Effect of inlet benzene concentration

The effect of inlet benzene concentration was studied in the range of 1.5-6.0 g m-3 during a biofil-tration period of 65 days. In order to acclimate the microbial culture to higher VOC concentrations, the concentration of input benzene was increased step-wise by maintaining an inlet concentration of 1.5 g m-3 for the first 16 days followed by 3.2 g m-3 during the second phase of 17-32 days of operation. The outlet concentrations of benzene were monitored once in 24 h and the removal efficiency was calculated. The vari-ation in removal efficiency during the different phases is presented in Figure 2. The maximum removal effi-ciency obtained was 99% with the lowest benzene concentration and the efficiency dropped to 91.8, 85.1 and 76%, respectively, with the inlet concentrations of 3.2, 4.8 and 6.0 g m-3, respectively. The experimental data confirmed the decrease in the removal efficiency and increase in exit VOC concentration when the inlet benzene concentration was increased. Excessive addition of input benzene beyond the threshold with-standing ability of microbes was reported to be a reason for this behaviour [26]. At higher inlet benzene concentrations,a transient state induced by high con-centration shock to microorganism was reported to occur and it leads to kinetic limitation. In addition, dry-ing of the bed axially, channeling of air stream due to biomass accumulation and product inhibition were reported to be the other factors [8].

Elimination capacity, defined as the amount of pollutant degraded per unit time, normalized to the packed bed volume is reported to be affected by the inlet loading of benzene. The influence of inlet ben-zene loading rate on the elimination capacity was stu-died in the range of 0-306 g m–3 h-1. From Figure 3, a linear relationship between elimination capacity and loading rate was observed. A linear relation was rep-orted in the biofiltration study on hydrogen sulfide using granular activated carbon [27]. The maximum elimination capacity achieved was 192.7 g m–3 h–1 as shown in the plot which is comparatively higher than the capacities of 3.8 and 44.9 g m–3 h–1 reported on other benzene biofiltration studies [6,23]. The rate of increase in elimination capacity was observed to be slower at higher loading rates of benzene. This phe-nomenon could be related to the attainment of maxi-mum removal capacity of microorganisms. Biofiltra-tion studies on hydrogen sulfide using pine bark filter media reported a similar relationship between elimin-ation capacity and inlet loading rate [28]. The leach-ate was collected periodically from the tail end of the column and its volume was approximately 250 mL per day.

Effect of EBRT

The flow rate of the benzene laden air is iden-tified as an important process variable as it decides the quantity of pollutant to be degraded per unit time. In this study, the influence of flow rate (or EBRT) was studied in the range of 1.2-4.7 min. Figure 4 presents a plot of EBRT versus removal efficiency attained at different times. At increased EBRT, the time of expo-sure of microorganism to the target pollutant was high and could possibly resulted in better removal effici-ency [19,26]. It was observed that when the inlet ben-zene concentration was low in the range of 1.5-3.0 g m-3, the removal efficiencies achieved at lowest flow

Figure 2. Biofiltration results for benzene removal at different inlet loading rates.


541

rate were higher by 20%. But, at higher benzene concentrations of 4.5 and 6.0 g m-3, the effect is less pronounced with a reduced net difference in removal efficiency.

Effect of biofilter height

The biofilter reactor employed consisted of four different sections with different biomass distributions. In order to identify the relative contribution of each

section in benzene degradation, the concentration profile was studied axially and plotted in Figure 5. The lowest section of the biofilter contributes to 40-45% of the total removal while the other sections degrade the remaining benzene. The reasons reported to be res-ponsible for better removal at the section-1 were better biomass distribution and moisture content. During the course of biofiltration, the temperature of

Figure 3. Effect of inlet loading rate on elimination capacity of benzene.

Figure 4. Effect of EBRT on benzene removal efficiency.

Figure 5. Concentration profile of benzene along the biofilter height.


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the bed is expected to increase which could affect the moisture content at the top sections of the biofilter. Since the biofilter was operated in up-flow mode, the driving force varies from section to section. The local benzene concentration was high at the lowest section and lowest in the topmost section of the biofilter [6]. Higher microbial density and homogeneous biomass distribution in the lowest part of the bed could be the reasons for this behaviour. Moreover, the concen-tration gradients in the upper sections are compar-atively lower, which resulted in lower removal effici-encies. Also, the filter bed could be dry in the upper sections due to the exothermic nature of the bio reac-tion. More efficient removal of toluene was reported in the first section of a compost based biofilter [24]. Stu-dies on removal of xylene in the inlet loading range of 12-34 g m–3 h–1 reported most of the removal in the lower part of the biofilter column in a peat based bio-filter [23].

Variation of bed temperature

The temperature variations during the biofiltra-tion experiments were followed by recording the aver-age bed temperature. Figure 6 shows the interactive variation patterns in temperature and elimination cap-acity. As expected, the biodegradation reaction of benzene was found to be exothermic which is proved by increase in temperatures at higher elimination cap-acities and microbial metabolic activity causes the increase of temperature. The temperature of the bed increased from 26.6 to 29.7 °C when there is a cor-responding increase in elimination capacity from 16.8 to 192.7 g m–3 h–1. The increase in temperature within the mesophilic range was reported to favour better removal of benzene by enhancing the activity of mic-roorganisms [8].

Carbon dioxide production profile

The proposed biodegradation mechanism of benzene is as shown in Eq. (6), where the possible products are carbon dioxide, water and biomass:

6 6 2 2 2C H O CO H O e( biomass)a b c d+ → + + (6)

The carbon dioxide production profile was rec-orded and plotted against elimination capacity in Fig-ure 7. A linear relationship represented by an equa-tion CPR = 1.76EC + 18.6 was found out with a high value of correlation coefficient, R2 (> 0.99). When complete mineralization of benzene into water and carbon dioxide was assumed, the stoichiometric mole ratio between benzene and carbon dioxide is 1:6 and mass ratio could be 1:3.38. However, the actual con-version ratio was 1.76, which was lower than the theoretical value of 3.38. The difference in value was attributed to the possible consumption of benzene for the microbial growth inside the reactor during the bio-filtration process. Also, the carbon dioxide could have accumulated in the liquid phase in the form of carbo-nates and bicarbonates [29]. Studies on removal of toluene in peat based biofilter [30] and xylene in an inert filter media biofilter [2] reported actual con-version ratios lesser than the stoichiometric ratios.

Biomass profile during biofiltration

Biodegradation efficiency depends on the estab-lishment of uniform biofilm and growth intensity inside the biofilter column. The dry cell mass was measured in different sections during the benzene biofiltration experiments and plotted in Figure 8. In section 1 of the biofilter column, the dry cell mass concentration increased from 0.16 to 0.35 g g-1 of filter media and found to be the maximum biomass buildup compared

Figure 6. Temperature variation profile during the biofiltration experiments.


543

to other sections of the biofilter. This observation was supplemented by enhanced removal percentages at section-1. These results show the attainment of a stable microbial density which is higher than the initial biomass in the filter media. The cell mass build up was found to be less at the top section due to the lower availability of benzene.

Kinetic modeling

The removal rate of benzene in the immobilized cell biofilter was fitted to a modified Michaelis- Menten model, shown below in a linearized form as Eq. (7) [31]:

s s

max ln max

1 K KEC EC C EC

= + (7)

where ECmax (g m-3 h-1) is the maximum EC, Cln (g m-3) is the logarithmic mean of inlet and outlet benzene concentrations and Ks (g m-3) is the saturation cons-tant. The slope and intercept of the linear fit between

1/EC and 1/Cln plot shown in Figure 9 gives the values of the kinetic parameters, ECmax and Ks. The value of R2 was found to be 0.61. The kinetic cons-tants will depend on the microorganisms attached to the filter media. The values of ECmax and Ks were found to be 217.4 g m-3 h-1 and 3.54 g m-3, respect-ively. The value of ECmax observed in this study was found to be in the range of values reported for ethyl benzene removal using Macadamia ternifolia nut-shells as filter media [32]. The physical meaning of Ks corresponds to the benzene concentration that must be treated to achieve ECmax/2. A material having a small Ks value was reported to have a greater affinity to benzene and vice-versa. The value of Ks observed in this study was comparatively less than the values of 70 g m-3 reported with biofiltration of hydrogen sulfide in a novel media biofilter [28] and 47 g m-3 reported with biofiltration of hydrogen sulfide and ammonia in an alginate beads based biofilter [33].

Figure 7. Elimination capacity versus carbon dioxide production.

Figure 8. Biomass profile during benzene biofiltration.


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CONCLUSION

The performance of a biofilter to treat benzene at different inlet loading rates was evaluated using a novel tree bark filter medium. The influence of inlet benzene concentration on the removal efficiency was studied and the biofilter was found to handle high concentrations of benzene effectively. Higher reten-tion times or lower flow rates favoured better removal of benzene in the biofilter. The axial concentration profile of benzene in the biofilter column proved a larger percentage of benzene removal in the lowest part of the column reactor. Carbon dioxide production rate was compared with the elimination capacity of benzene and a linear relationship was proposed. Temperature variations were recorded and found to vary with elimination capacity changes. The biokinetic constants were calculated using a modified Michaelis- –Menten model. The results suggest that the date palm tree bark based biofilter is a suitable choice for treating benzene in the concentration range of 1.5-6.0 g m-3.

Acknowledgement

The authors acknowledge that this research leading to these results has received project funding from The Research Council of Oman under Research Agreement No.: ORG/SU/EBR/12/020. Also, the authors thankfully acknowledge the facilities provided by Sohar University, Oman.

REFERENCES

[1] A. Barona, A. Elias, R. Arias, E. Acha, I. Cano, Chem. Eng. Technol. 30 (2007) 1499-1505

[2] G. Gallastegui, A. A. Ramirez, A. Elias, J.P. Jones, M. Heitz, Bioresour. Technol. 102 (2011) 7657-7665

[3] European Union Regulation (EC) no 166/2006 of the Eur-opean parliament and of the council of 18 January 2006 concerning the establishment of a European Pollutant Release and Transfer Register and amending council dir-ectives 91/689/EEC and 96/61/EC, Official journal of the European Union 1 (2006) 33

[4] A.A. Hassan, G.A. Sorial, J. Hazard. Mater. 184 (2010) 345–349

[5] J.R .Robledo-Ortiz,., D.E. Ramirez-Arreola, A.A. Perez-Fonseca, C. Gomez, O. Gonzalez-Reynoso, J. Ramos- -Quirarte, R. Gonzalez-Nunez, Int. Biodeter. Biodeg. 65 (2011) 539–546

[6] Rahul, A.K. Mathur, S. Bala, C. Majumder, Bioresour. Technol. 125 (2012) 200–207

[7] C. Kennes, E.R. Rene, E.R., M.C. Viega, J. Chem. Technol. Biotechnol. 84 (2009)1419-1436

[8] D. Wu, X. Quan, X., Y. Zhao, S. Chen, J. Hazard. Mater. 136(2006) 288–295

[9] C. Kennes, M.C. Viega, Air pollution prevention and con-trol; bioreactors and bioenergy,John Wiley and sons, Chi-chester, 2013, p. 549

[10] B.T. Mohammad, M.C. Veiga C. Kennes, Biotechnol. Bio-eng .97 (2007)1423–1438

[11] E.R. Rene, D.V.S. Murthy, T. Swaminathan, Water Air Soil Pollut. 211 (2010) 79–93

[12] G. Bacquirezo, J.P. Maestre, T. Sakuma, M.A. Deshu-shes, X. Gamisans, D. Gabriel, J. Lafuente, Chem. Eng. J. 113 (2005) 205-214

[13] A. Jantschak, M. Daniels, R. Paschold, IEEE Transac-tions On Semiconductor Manufacturing 17 (2004) 255- –260

[14] D. Kim, Z. Cai, G.A. Zorial, Environ. Prog. 24 (2005) 155- –161

[15] S. Mudliar, B. Giri, K. Padoley, D. Satpute, R. Dixit, P. Bhatt, R. Pandey, A. Juwarkar, A. Vaidya, J. Environ. Manage. 91 (2010) 1039–1054

[16] E.H. Lee, H.W. Ryu, K.S. Cho, Bioresour. Technol. 100 (2009) 5656-5663

Figure 9. Kinetic model plot for biofiltration kinetics of benzene.


545

[17] K. Singh, R.S. Singh, B.N. Rai, S.N. Upadhyay, Bio-resour. Technol. 101 (2010) 3947-3951

[18] G. Moussavi, M.B. Bahadori, M. Farzadkia, A. Yazdan-baksh, M. Mohseni, Biochem. Eng. J. 45 (2009) 152-156

[19] V. Saravanan, N. Rajamohan, J. Hazard. Mater. 162 (2009) 981–988

[20] V. Saravanan, B. Ramya, M. Rajasimman, N. Rajamo-han, Water Air Soil Pollut. 224 (2013) 1445-1454

[21] H.H. Kwon, E.Y. Lee, K.S. Cho, H.W. Ryu, J. Microbiol. Biotechnol. 13 (2003) 70-76

[22] I. Garcia-Pena, I. Ortiz, S. Hernandez, S. Revah, Int. Biodeter. Biodeg. 62 (2008) 442–447

[23] L. Sene, A. Converti, M.G.A. Felipe, M. Zilli, Bioresour. Technol. 83 (2002) 153–157

[24] E.R. Rene, D.V.S. Murthy, T. Swaminathan, Maced. J Chem. Eng. 28 (2009) 119–123

[25] P.M. Heynderickx, J.W. Thybaut, ,H. Poelman, D. Poel-man, G.B. Marin, Appl. Catal. 90 (2009) 295-306

[26] H. Elmrini, N. Bredin, Z. Shareefdeen, M. Heitz, Chem. Eng. J. 100 (2004) 149–158

[27] C.Rattanapan, P. Boonsawang, D. Kantachote, Bio-resour. Technol.100 (2009) 125-130

[28] E. Dumont, Y. Andres, P. Le Cloirec, F. Gaudin, Bio-chem. Eng. J .42 (2008) 120-127

[29] E.R. Rene, B.T. Mohammad, M.C. Viega, C. Kennes, Bioresour. Technol. 116 (2012) 204-213

[30] F.J. Alvarez-Hornos , C. Gabaldon , V. Martínez-Soria, P. Marzal, J.M. Penya-Roja. J. Chem. Technol. Biotechnol. 83 (2008) 643–653

[31] M.Hirai, M. Ohtake, M. Shoda, J. Ferment. Bioeng. 70 (1990) 334-339

[32] D. Volckaert, J.A. Hornos, P.M. Heynderickx ,C. Kittikoon, H.V. Langenhove, J. Chem. Technol. Biotechnol. 88 (2013) 81-87

[33] Y.C. Chung, C. Huang, C.P. Tseng, Chemosphere 43 (2001) 1043-1050.

RAJAMOHAN NATARAJAN1

JAMILA AL-SINANI1

SARAVANAN VISWANATHAN2 1Faculty of engineering, Sohar

University, Sohar, Oman 2Department of Chemical Engineering,

Annamalai University, India

NAUČNI RAD

PROCENA PERFORMANSI I KINETIKA UKLANJANJA BENZENA U BIOFILTERU NA BAZI KORE DRVETA SA STRUJANJEM NAVIŠE

U radu je pogodnost primene kore drveta Phoenix dactylifera kao novog filter medija u biofilteru sa strujenjem naviše i mešanom kulturom za uklanjanje benzena. Eksperimenti su rađeni sa različitim koncentracijama benzena (1,5–6,0 g m-3) i vremenom zadržavanja u filter bez biomaterijala (EBRT = 1,2- 4,7 min). Nađeno je da eliminacioni kapacitet linearno varira sa brzinom ulaznih količina benzena u opsegu od 0-306 g.m-3 h-1. Pri koncentraciji benzena od 1,5 g m-3 postiže se efikasnost uklanjanja od 99%. Ona opada sa porastom koncentracije benzena. Pri manjim protocima efikasnost uklanjanja benzena je veća. Ana-liziran je koncentracioni profil za različite visine filter medija. Pošto temperatura raste za vreme biofiltracije eksperiment potvrđuje egzotermnu prirodu biofiltracije. Brzina stvaranja ugljen dioksida u odnosu na kapacitet eliminacije data je jednačinom CPR = 1.76EC ++ 18.6. Primenom Michaelis-Menten modela nađene su kinetičke konstante, kao što su: maksimalni eliminacioni kapacitet 217,4 g m-3 h-1 i konstanta zasićenja 3,54 g m-3.

Ključne reči: kinetika, benzen, zagađenje.




547

D.TIROUTCHELVAME1

V. SIVAKUMAR2

J. PRAKASH MARAN3 1Department of Food Processing

and Engineering, Karunya University, Coimbatore, Tamil

Nadu, India 2Department of Chemical

Engineering, AC Tech Campus, Anna University, Chennai, Tamil

Nadu, India 3 Department of Food Technology,

Kongu Engineering College, Perundurai, Erode, Tamil Nadu,

India

SCIENTIFIC PAPER

UDC 66.093.48:58(540):544

DOI 10.2298/CICEQ140712011T

MASS TRANSFER KINETICS DURING OSMOTIC DEHYDRATION OF AMLA (Emblica officinalis L.) CUBES IN SUGAR SOLUTION

Article Highlights • Osmotic dehydration of amla cubes were studied using RSM • Mass transfer properties and quality characteristics of dehydrated amla cubes were

studied • Second order polynomial models were developed for responses • Optimization of osmotic dehydration process was done by desired function metho-

dology Abstract

A four-factor three-level Box-Behnken response surface design was employed in this study to investigate and optimize the effect of process variables (osmo-tic solution concentration, fruit to liquid ratio, temperature and dehydration time) on mass transfer properties such as weight reduction, solute gain, water loss, rehydration ratio, shrinkage and overall acceptability of the osmotically dehydrated amla cubes. The cubes of uniform size (10 mm×10 mm×10 mm) were impregnated into sugar solution of different solution concentration (30-50 °Brix), temperature (30-50 °C), fruit to liquid ratio (1:5-1:15 w/V) and time (30-–180 min). It was observed from the results that the process variables have significant effects on osmotic dehydration process. The optimum condition was found to be: sugar concentration of 50 °Brix, solution temperature of 30 °C, fruit to liquid ratio of 1:5 and immersion time of 133 min, respectively. The mic-rostructural changes during osmotic dehydration were also investigated using scanning electron microscopy (SEM).

Keywords: amla, osmotic dehydration, response surface methodology, microstructure.

Fruits and vegetables are considered to be important components of life for the health of human beings by providing the required nutrients. Since fruits and vegetables are highly perishable in nature, they should be processed quickly after harvest in order to reduce the post-harvest losses during glut period. As a perishable commodity, they are available at much cheaper in terms of selling price during the peak season, and can also lead to more financial losses to the grower resulting in the spoilage in larger quan-tities. The preservation of fruits and vegetables can

Correspondence: V. Sivakumar, Department of Chemical Eng-ineering, AC Tech Campus, Anna University, Chennai, Tamil Nadu, India. E-mail: [email protected] Paper received: 12 July, 2014 Paper revised: 16 March, 2015 Paper accepted: 20 April, 2015

prevent a huge wastage and make them available during the off-season at remunerative prices [1].

The removal of water from solid food is a form of food preservation, inhibiting the growth of microorg-anisms, besides preventing a large part of bioche-mical reactions that occur due to the presence of moisture [2]. The dehydration process of fruits and vegetables provides many advantages, such as red-uced weight, inexpensive packaging, dry shelf stab-ility and negligible deterioration in quality due to enzymatic changes. However, this method has some disadvantages related to the preparation and handling of large volumes of osmotic solutions, high water con-sumption and losses of soluble nutritional compounds in the osmotic solution. Proper management and reuse of the spent osmotic solution need to be addressed in order to develop this process to be eco-nomically viable and cost effective.

D.TIROUTCHELVAME et al.: MASS TRANSFER KINETICS DURING OSMOTIC… Chem. Ind. Chem. Eng. Q. 21 (4) 547−559 (2015)

548

Osmotic dehydration is the process of partial removal of water from fruits and vegetables using hypertonic solutions. These solutions can contain one or more solutes. For fruits, sugar is the commonly used solute. Other solutes that are used as osmotic agents include glucose, fructose, maltodextrose and corn syrup [3]. Common salt (sodium chloride) is the most used solute for vegetables. In some cases, a combination of solutes can also be used. Osmotic dehydration is governed by the osmotic pressure dif-ference between the food material (hypotonic medium) and concentrated osmotic solution (hyper-tonic medium) [4]. The cell membrane works as a semi-permeable tissue and allows water to pass through faster than solutes [5]. The mass transfer rate is higher at the beginning of the process because of the largest difference in the osmotic pressure between the osmotic solution and cell tissue of the material and less mass transfer resistance at the ini-tial stage of the process [6]. The rate of water removal from the food material and changes in the chemical composition depend on the type of osmotic solute used, its concentration, temperature, time of impreg-nation in the solution, fruit to solution ratio, size and kind of the material and the type of apparatus used. During osmotic dehydration, two main mass fluxes (water loss and solid gain) take place as counter-current. The effectiveness of the osmotic treatment can be evaluated by the ratio of water loss to solid gain, considering that the water removal must be greater than the solid intake [7]. The low values of this ratio establish the best condition of osmotic dehyd-ration [8].

Amla (Emblica officinalis L.), commonly called as Indian gooseberry is an important seasonal fruit crop of the Indian subcontinent [9]. The plant has the ability to grow in wastelands and cultivation area has increased in the recent years [10]. Owing to hardy nature, suitability to various wastelands, high product-ivity/unit area (15-20 t/ha), nutritive and therapeutic value, amla is becoming more and more commercially important now a days. Amla is highly nutritious and is an important dietary source of Vitamin C, minerals and amino acids. It contains 500-1500 mg of ascorbic acid per 100 g of pulp [11]. The medicinal properties of amla were studied as a preventive and therapeutic drug for cancer in humans [12]. Studies have also been performed for the evaluation of amla properties on in vivo tests [13].

Amla is highly perishable in nature and it can be stored under atmospheric conditions only for about 5-6 days after harvesting [14]. The storage and shelf life of the fruits can be increased by adopting appropriate

processing methods and it could eliminate the post- -harvest losses up to 30% [15]. The methods adopted for extending the shelf life of amla fruit include cold storage, sun drying and hot air drying or by value addition of the fruits by converting to murabba, pickle, juice, syrup, squash and dehydrated powder [16]. Among the various drying methods available, osmotic dehydration is one of the most simple and inexp-ensive alternate processes. It is an energy-saving and low capital investment process that offers a way to make available this highly perishable and valuable crop for the regions away from production zones and also during off-season. The cultivation of amla has increased, thus augmenting the post-harvest storage problems. Development of shelf stable products from amla is important for the reduction of post-harvest losses. Hence, the objective of the present research was to evaluate and optimize the influence of the process variables such as osmotic solution concen-tration, time of dehydration, temperature and fruit to liquid ratio on the osmotic dehydration characteristics (water loss, solid gain, weight reduction, rehydration ratio and shrinkage) of amla cubes in sugar solution using statistical experimental design. In addition, the overall acceptability of the product was also analyzed with the help of trained panelist using a nine point hedonic scale sensory evaluation method. Scanning electron microscopy (SEM) was also used to analyze the microstructural changes during osmotic dehyd-ration of amla.


Raw materials

Fresh amla fruits (uniform size, shape, and mat-urity) were procured from local market near Coim-batore, Tamil Nadu, India. Osmotic solutions with different concentration (30-50 °Brix) were prepared by dissolving appropriate amount of sugar in distilled water. The concentrations (°Brix) of the prepared osmotic solutions were checked by using a hand ref-ractometer. The initial moisture content of the raw fruit and the final moisture content after impregnation in sugar solution were determined by following AOAC procedure [17]. The initial moisture content (wet basis) of fresh amla fruit was 80.5% and the final moisture content after osmotic treatment in sugar sol-ution was found to be 61.5%.

Experimental procedure

The amla fruit was cut in to 1 cm3 (10 mm×10 mm×10 mm) size cubes for each experiment. The amla fruits were washed in running tap water in order


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to remove any adhering foreign matters on the sur-face. The outer skin of the fruit is waxy in nature which will resist the mass transfer rate. Hence, the fruits were blanched for 5 min in hot water, which could remove the unacceptable odor and to increase the mass transfer by loosening the tissues of the fruit. The fruits were then removed from hot water and the excess moisture on the surface was removed by using muslin cloth. The seeds were removed by using seed remover and the pulp of the fruit was used for further experimental analysis.

The desired concentration of osmotic solution of sugar was prepared and the known weight of amla cubes were immersed in Erlenmeyer flasks containing osmotic solutions of different concentrations (30-50 °Brix) at different temperatures (30-50 °C), fruit to liquid ratio (1:5-1:15 w/V) and time (30-180 min). From the preliminary experimental results, the pro-cess variables and their ranges were selected. The osmotic dehydration process was carried out in a temperature-controlled chamber. The Erlenmeyer flasks were covered with a plastic wrap during the experiments in order to prevent evaporation of the osmotic solution. During osmotic treatment, at a par-ticular interval of time, the cubes were removed from the osmotic solution and weighed after removing the solution adhering on the surface using filter paper (Whatman No. 1). The experiments were carried out in randomized order to minimize the variability in the observed responses due to extraneous factors. All the experiments were performed in triplicate and the mean value was used for the determination of water loss, weight reduction and solid gain.

Mathematical calculations

Determination of mass transfer properties In osmotic dehydration, both water loss and

solid gain take place simultaneously. The reduction in weight is attributed to the loss of water from the sample and increase in the weight of the sample due to solute gain from the osmotic solution. The evalu-ation of mass transfer between the solution and samples during osmotic dehydration process were estimated by using the parameters such as weight reduction (WR), solid gain (SG) and water loss (WL) and the parameters were calculated by using the following equations:

( ) 0

0

% 100 tW WWRW

−= (1)

( ) 0

0

% 100 tS SSGW−= (2)

( )%WL WR SG= + (3)

where W0 is the initial weight of amla cubes (g), Wt the weight of amla cubes after osmotic dehydration for any time t (g), S0 is the initial dry weight of amla (g), and St is dry weight of amla after osmotic dehydration for any time t (g).

Estimation of quality parameters The quality parameters such as rehydration ratio

(RR) and shrinkage (SH) of the osmotic dehydrated amla cubes were studied in the present work. The rehydration characteristics of the osmotically dehyd-rated amla cubes were determined by soaking a known amount of sample in 50 ml of water and kept at room temperature [18] until constant weight was attained. The rehydration ratio was computed by using the formula:

Weight of rehydrated amla cube (g)(%) 100

Weight of dehydrated amla cube (g)RR = × (4)

Shrinkage (SH) of the dehydrated sample was determined by using the following equation:

0

(%) 100 1 iVSHV

= −

(5)

where Vi is the volume displaced by the dehydrated sample and V0 is the volume displaced by the fresh sample [19].

Organoleptic evaluation

Overall acceptability (OA) of dehydrated amla cubes was evaluated by a trained panel of 10 mem-bers of all age groups (15-50). The samples were served in plastic cups, coded with three-digit ran-domly selected numbers to the panelists in a random order. The panelists were instructed to cleanse their palates using water between the samples. All the panelists evaluated the odor and taste of the samples using quantitative descriptive analysis (QDA) tech-nique with a line scale of 0-9 [20] where 0 and 9 are assigned to negative and positive intensity of overall acceptability of dehydrated amla cubes. The overall acceptability was computed by the average scores of all the 10 panelists.

Response surface methodology modeling

Response surface methodology (RSM) is an empirical statistical modeling technique employed for multiple regression analysis using quantitative data obtained from properly designed experiments to solve multivariate equations simultaneously. A Box Behn-ken Design (BBD) with four factors at three levels was used to design the experiments and it is exhibited in


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Table 1. The process parameters (independent vari-ables) selected for the optimization were osmotic solution concentration (X1), fruit to liquid ratio (X2), osmotic temperature (X3) and osmotic dehydration time (X4). The number of experiments (N) required for the development of BBD is defined as N = 2k(k-1) + + Co (where k is the number of factors and Co is the number of central point) [21]. The design included 29 experiments and with 5 central points. Each inde-pendent variable was coded at three levels between +1, 0 and -1, whereas osmotic solution concentration: 30-50 °Brix, fruit to liquid ratio: 1:5-1:15 g/ml, osmotic temperature: 30-50 °C and time: 30-180 min. Coding of the variables was done according to the following equation:

cpii

i

x xx

x−

=Δ

, 1,2,3...,i k= (6)

where xi is the dimensionless value of an independent variable; Xi is the real value of an independent variable; xcp is the real value of an independent vari-able at the center point; and ΔXi is the step change of real value of the variable i corresponding to a vari-ation of a unit for the dimensionless value of the vari-able i.

Performance of the process was evaluated by analyzing the responses (Y), which depend on the input factors x1, x2,…,xk, and the relationship between the response and the input process parameters is described by:

( )1 2, ,..., kY f x x x e= + (7)

where f is the real response function the format of which is unknown and e is the error which describes the differentiation [22].

A second-order polynomial equation was used to fit the experimental data to identify the relevant model terms using statistical software (Design Expert 8.0.7.1). A quadratic model, which also includes the linear model, can be described as

20 1 1 2

Yk k k

j j jj j ij i j ij j i jx x x x eβ β β β

= = < == + Σ + Σ + Σ Σ + (8)

where xi and xj are variables (i and j range from 1 to k); β0 is the model intercept coefficient; βj, βjj and βij

are interaction coefficients of linear, quadratic and the second-order terms, respectively; k is the number of independent parameters (k = 4 in this study); and ei is the error [23].

The statistical analysis was performed using Design Expert Statistical Software package 8.0.7.1 (Stat Ease Inc., Minneapolis, MN, USA). The experi-mental data was analyzed using multiple regressions and the significance of regression coefficients was evaluated by F-test. Modeling was started with a quadratic model including linear, squared and inter-action terms and the model adequacies were checked in terms of the values of R2, adjusted R2 and pre-diction error sum of squares (PRESS). The significant terms in the model were found by Pareto analysis of variance (ANOVA) for each response at significance level of 95% and ANOVA tables were generated. The regression coefficients were used to make statistical calculations to generate response surface plots from the regression models.

Microstructure analysis

The fresh and osmotically treated (optimal con-dition) amla pieces were examined using scanning electron microscopy (SEM) in order to determine the effect of osmotic dehydration process on the micro-structure of the tissue. Samples were cut into cubes with a sharp blade and mounted on aluminium SEM stubs for gold coating with a fine coat. The micro-structure of the tissue was examined by a JEOL scan-ning electron microscope (JSM-6390) and the images were recorded at the magnification of 100×.


Model fitting and statistical analysis

A total number of 29 experiments were per-formed with different combinations of process vari-ables in order to study and optimize the combined effect of independent variables (osmotic solution con-centration, fruit to liquid ratio, osmotic temperature and time) on the responses (WR, SG, WL, RR, SH and OA) and the results are shown in Table 2.

By applying multiple regression analysis on the experimental data, Design-Expert software generated the second-order polynomial equation, which can

Table 1. Coded and uncoded values of process variables and their levels during osmotic dehydration of amla cubes in sugar solution

Independent variables Coded levels −1 0 +1

Solution concentration, °Brix X1 30 40 50

FL ratio, g/ml X2 1:5 1:10 1:15

Temperature, °C X3 30 40 50

Time, min X4 30 105 180


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express the relationship between process variables and the responses. The final equations obtained in terms of coded factors are as follows:

Pareto analysis of variance (ANOVA) was used to analyze the experimental data and the results are listed in Table 3. The higher model F-value (84.10 for

Table 2. Box-Behnken experimental design matrix with observed values of responses for the osmotically treated amla cubes in sugar solution; WR: weight reduction, SG: solid gain, WL: water loss, RR: rehydration ratio, OA: overall acceptability, SH: shrinkage

Std. order X1 X2 X3 X4 WR / % SG / % WL / % RR / % OA SH / %

1 -1 -1 0 0 22.91±1.03 7.75±0.43 28.19±1.21 4.6±0.13 6.2±0.18 3.8±0.23

2 1 -1 0 0 32.55±1.18 17.35±0.65 37.84±1.30 14.3±0.27 7.9±0.21 11.9±0.48

3 -1 1 0 0 22.34±1.09 7.18±0.23 27.62±1.26 4.0±0.14 6.1±0.19 3.4±0.09

4 1 1 0 0 26.26±1.24 11.06±0.43 31.51±1.32 8.0±0.32 6.8±0.22 6.6±0.31

5 0 0 -1 -1 27.30±1.17 12.11±0.26 32.54±1.05 9.0±0.37 7.0±0.36 7.5±0.28

6 0 0 1 -1 31.46±1.13 16.26±0.68 36.71±1.28 13.2±0.28 7.7±0.43 11.0±0.45

7 0 0 -1 1 23.86±1.31 8.71±0.29 29.10±1.15 5.6±0.17 6.4±0.61 4.6±0.17

8 0 0 1 1 33.68±1.26 18.53±0.41 38.93±1.29 15.4±0.33 8.1±0.24 12.8±0.29

9 -1 0 0 -1 24.56±1.14 9.36±0.09 29.81±1.14 6.3±0.19 6.5±0.08 5.2±0.22

10 1 0 0 -1 32.95±1.21 17.75±0.62 38.23±1.35 14.7±0.52 8.0±0.25 12.2±0.26

11 -1 0 0 1 24.55±1.09 9.35±0.33 29.81±1.26 6.3±0.18 6.5±0.36 5.2±0.17

12 1 0 0 1 33.87±1.21 18.71±0.53 39.11±1.17 15.6±0.53 8.2±0.28 13.0±0.26

13 0 -1 -1 0 26.96±1.15 11.76±0.27 32.24±1.24 8.7±0.16 7.1±0.23 7.2±0.19

14 0 1 -1 0 17.14±1.04 1.94±0.06 22.38±1.18 1.2±0.11 5.2±0.23 1.0±0.06

15 0 -1 1 0 28.05±1.12 12.86±0.47 33.30±1.27 9.8±0.47 7.0±0.18 8.1±0.25

16 0 1 1 0 31.44±1.36 16.25±0.18 36.73±1.35 13.2±0. 53 7.7±0.17 11.0±0.39

17 -1 0 -1 0 19.48±1.07 4.29±0.08 24.76±1.13 1.2±0.12 5.6±0.37 1.0±0.05

18 1 0 -1 0 31.21±1.27 16.06±0.41 36.46±1.24 12.9±0.61 7.7±0.19 10.8±0.24

19 -1 0 1 0 31.44±1.32 16.24±0.29 36.73±1.28 13.2±0.53 7.7±0.31 11.0±0.27

20 1 0 1 0 37.11±1.35 21.91±0.63 42.35±1.35 18.8±0.61 8.7±0.22 15.7±0.39

21 0 -1 0 -1 26.83±1.17 11.63±0.25 32.11±1.23 8.5±0.24 6.9±0.27 7.1±0.21

22 0 1 0 -1 28.11±1.09 12.92±0.37 33.36±1.19 9.8±0.29 7.1±0.37 7.6±0.14

23 0 -1 0 1 27.46±1.05 12.27±0.31 32.71±1.16 9.2±0.27 7.0±0.62 7.6±0.18

24 0 1 0 1 23.90±1.13 8.71±0.26 29.19±1.14 5.6±0.18 6.4±0.65 4.7±0.21

25 0 0 0 0 39.29±1.28 24.10±0.72 44.53±1.25 21.0±0.67 9.1±0.53 17.5±0.29

26 0 0 0 0 39.29±1.25 24.11±0.63 44.53±1.27 21.0±0.62 9.1±0.45 17.5±0.22

27 0 0 0 0 39.29±1.21 24.14±0.68 44.53±1.23 21.0±0.58 9.1±0.32 17.5±0.36

28 0 0 0 0 39.29±1.19 24.10±0.47 44.54±1.19 21.0±0.64 9.1±0.31 17.5±0.32

29 0 0 0 0 39.29±1.16 24.10±0.61 44.54±1.28 21.0±0.39 9.1±0.56 17.5±0.41

1 2 3 1 2 1 3 2 3 2 4 3 4

2 2 2 21 2 3 4

39.29 4.06 1.301 3.94 1.43 1.52 3.30 1.21 1.42

4.97 8.13 4.98 5.05

WR X X X X X X X X X X X X X

X X X X

= + − + + − + − + −

− − − − (9)

1 2 3 1 2 1 3 2 3 2 4 3 4

2 2 2 21 2 3 4

24.11 4.06 1.30 3.93 1.43 1.52 3.30 1.21 1.42

4.97 8.13 4.98 5.06

SG X X X X X X X X X X X X X

X X X X

= + − + + − + − + −

− − − − (10)

1 2 3 1 2 1 3 2 3 2 4 3 4

2 2 2 21 2 3 4

44.53 4.05 1.30 3.94 1.44 1.52 3.32 1.19 1.41

4.95 8.11 4.98 5.05

WL X X X X X X X X X X X X X

X X X X

= + − + + − + − + −

− − − − (11)

1 2 3 1 2 1 3 2 3 2 4 3 4

2 2 2 21 2 3 4

17.50 3.38 0.97 3.12 1.19 1.26 2.27 0.87 1.18

4.20 6.66 3.97 4.34

SH X X X X X X X X X X X X X

X X X X

= + − + − − + − + −

− − − − (12)

1 2 3 1 2 1 3 2 3 2 4 3 4

2 2 2 21 2 3 4

21.00 4.06 1.11 3.75 1.43 1.52 2.73 1.21 1.42

5.06 7.94 4.79 5.15

RR X X X X X X X X X X X X X

X X X X

= + − + − − + − + −

− − − − (13)

1 2 3 1 2 1 3 2 3 2 4 3 4

2 2 2 21 2 3 4

9.12 0.71 0.23 0.66 0.25 0.27 0.67 0.20 0.25

0.87 1.42 0.87 0.89

OA X X X X X X X X X X X X X

X X X X

= + − + − − + − + −

− − − − (14)


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WR, 83.27 for SG, 83.89 for WL, 80.78 for RR, 94.65 for SH and 80.55 for OA) and the associated lower p-values (p < 0.0001) demonstrated the significance of developed models and also indicated that most of the variation in the responses could be explained through the regression equations. The high value of R2 (0.9882 for WR, 0.9881 for SG, 0.9882 for WL, 0.9878 for RR, 0.9875 for SH and 0.9867 for OA) and adj-R2 (0.9765 for WR, 0.9763 for SG, 0.9764 for WL, 0.9755 for RR, 0.9791 for SH and 0.9755 for OA) clearly demonstrated that the form of the model chosen to represent the actual relationship between the response and independent variables is well cor-related and accurate. Low values of coefficient of vari-ance (3.24 for WR, 6.66 for SG, 2.75 for WL, 8.33 for RR, 7.73 for SH and 2.32 for OA) exhibited the high degree of precision and good reliability of the con-ducted experiments. In this study, the adequate pre-cision (signal to noise ratio) was found to be > 29 for all the responses, which indicated the best fitness of the developed models.

Diagnostics of model adequacy

Generally, it is important to confirm that the fitted model gives a sufficient approximation to the actual values. Unless the model shows a satisfactory fit, pro-ceeding with an investigation and optimization of the

fitted response surface likely gives poor or misleading results. In addition to determination coefficient, the adequacy of the models was also evaluated by the residuals (difference between the observed and the predicted response value) and the influence plots for the experimental data obtained from this study. Diag-nostic plots such as predicted versus actual (Figure 1) help us to evaluate the model suitability and find out the relationship between predicted and experimental values. The data points on this plot lie reasonably close to the straight line and indicated that an ade-quate agreement between real data and the data obtained from the models. Hence, trends observed in Figure 1 revealed that no obvious patterns were found and residuals appeared to be randomly scattered.

Effect of process variables

To understand the interaction between the inde-pendent variables and dependent variables, three dimensional (3D) response surface plots were plotted from the developed model. In this study, the model has more than two factors. Hence, the 3D plots were drawn by maintaining two factors at constant level (in turn at its central level), whereas the other two factors were varied in their range in order to understand their main and interactive effects on the dependent vari-

Table 3. Analysis of variance (ANOVA) for the observed responses; DF: degree of freedom, RC: regression coefficient

Source DF WR / % SG / % WL / % RR / % OA / % SH / %

RC p value RC p value RC p value RC p value RC p value RC p value

Model 14 39.29 < 0.0001 24.11 < 0.0001 44.53 < 0.0001 21 < 0.0001 9.12 < 0.0001 17.50 < 0.0001

X1 1 4.06 < 0.0001 4.06 < 0.0001 4.05 < 0.0001 4.06 < 0.0001 0.71 < 0.0001 3.38 < 0.0001

X2 1 -1.30 0.0004 -1.30 0.0004 -1.30 0.0004 -1.11 0.0013 -0.23 0.0004 -0.97 0.0005

X3 1 3.94 < 0.0001 3.93 < 0.0001 3.94 < 0.0001 3.75 < 0.0001 0.66 < 0.0001 3.12 < 0.0001

X4 1 -0.32 0.2660 -0.31 0.2823 -0.33 0.2609 -0.32 0.2639 -0.05 0.2972 -0.22 0.3189

X12 1 -1.43 0.0101 -1.43 0.0105 -1.44 0.0097 -1.43 0.0098 -0.25 0.0114 -1.19 0.0061

X13 1 -1.52 0.0071 -1.53 0.0071 -1.52 0.0070 -1.52 0.0069 -0.27 0.0081 -1.26 0.0042

X14 1 0.23 0.6341 0.24 0.6241 0.22 0.6548 0.23 0.6326 0.04 0.6413 0.20 0.6058

X23 1 3.30 < 0.0001 3.30 < 0.0001 3.32 < 0.0001 2.73 < 0.0001 0.67 < 0.0001 2.27 < 0.0001

X24 1 -1.21 0.0248 -1.21 0.0252 -1.19 0.0267 -1.21 0.0242 -0.20 0.0326 -0.87 0.0346

X34 1 1.42 0.0108 1.42 0.0110 1.42 0.0108 1.42 0.0105 0.25 0.0122 1.18 0.0065

X12 1 -4.97 < 0.0001 -4.97 < 0.0001 -4.95 < 0.0001 -5.06 < 0.0001 -0.87 < 0.0001 -4.20 < 0.0001

X22 1 -8.13 < 0.0001 -8.14 < 0.0001 -8.11 < 0.0001 -7.94 < 0.0001 -1.43 < 0.0001 -6.66 < 0.0001

X32 1 -4.98 < 0.0001 -4.98 < 0.0001 -4.98 < 0.0001 -4.79 < 0.0001 -0.87 < 0.0001 -3.97 < 0.0001

X42 1 -5.05 < 0.0001 -5.06 < 0.0001 -5.05 < 0.0001 -5.15 < 0.0001 -0.89 < 0.0001 -4.34 < 0.0001

R2 0.988 0.988 0.988 0.988 0.988 0.990

Adj-R2 0.976 0.976 0.976 0.976 0.975 0.979

Pre-R2 0.932 0.932 0.932 0.930 0.929 0.940

CV / % 3.24 6.66 2.75 8.33 2.32 7.73

Adeq. Pre.

31.25 31.09 31.24 29.44 31.13 31.94


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Figure 1. Model adequacy plots (experimental vs. predicted) for responses (WR: weight reduction, SG: solid gain, WL: water loss,

RR: rehydration ratio, SH: shrinkage, OA: overall acceptability).

ables. The model was also used to locate the opti-mum conditions.

Mass transfer properties

At the beginning of the process, due to high osmotic driving force between the concentrated sol-

ution and the fresh sample, the rate of water removal and solid gain was relatively high. The osmosis effect increased with the increasing sugar concentration from 30-45 °Brix (Figure 2a-b). Increase in solution concentration up to 45 °Brix resulted in an increase in the osmotic pressure gradients and hence, higher


554

Figure 2. Response surface plots for different mass transfer parameters (WL: water loss, WR: weight reduction, SG: solid gain) during

osmotic dehydration of amla cubes.

water loss (and solid uptake) values throughout the osmosis period were obtained. When the osmotic sol-ution concentration was increased, water loss and solid gain took place in parallel mode; the rate of water loss is always higher than the solid gain. In osmotic dehydration, the concentration gradient between the intracellular fluid and osmotic solution create a difference of osmotic pressure, which leads

to diffusion of water and solid molecules through the semi-permeable membrane of this fruit to achieve osmotic equilibrium. Thus, the increase in solute con-centration led to increases in SG and WL. Further inc-rease of sugar concentration reduced the water loss that might have led to sugar gain by the fruits, which was not desirable [24]. This is attributed to the dif-fusion of water from dilute medium to concentrated


555

solution (hypertonic solution) through a semi-perme-able membrane until the concentration equilibrium was reached. The driving force in this process is the water activity gradient caused due to the osmotic pressure. For solute concentrations of above 50 ºBrix and below 30 °Brix, there was impregnation and crys-tallization of sugar and poor moisture removal res-pectively. This strongly suggested that for optimal osmotic dehydration, the sugar concentrations should be in the range of 40-50 °Brix.

High temperatures combined with high concen-tration of osmotic solution were shown to facilitate osmotic dehydration. Increase in temperature (up to 45 °C) led to more water loss than solid gain, which caused an increase in the weight reduction. This phenomenon is attributed to the diffusion difference between water and solutes as related to their molar masses [25-28]. Further increase in temperature affects the semi-permeability of the cell walls and reduces the rate of osmosis. This may be due to red-uction in viscosity of hypertonic solution and increase in diffusion coefficient of water increased at high tem-perature [29,30].

Osmotic treatment time is one of the most influ-ential variables during osmotic dehydration of fruits, which is due to the fact that the WL, WR and SG were based on the time. From the results, it was observed that increasing time (0 to 135 min) resulted in an ini-tial increase of the WL, WR (Figure 2c-d) and SG (Figure 2e-f), followed by a decrease. This can be explained by the ionization characteristics and low molecular weight of sugar that allow it to diffuse easily into the product and increase the driving force for dehydration. On the other hand, SG increased in the early stages, remained almost constant for a short period of time and finally showed a decreasing trend. This declining trend in SG at the end of the process could be attributed to the loss of some original solids in amla due to the osmotic driving force between the amla and the surrounding sugar solution [31]. But in this study, osmotic dehydration time did not statis-tically have a significant effect of the process (p < < 0.05, Table 3).

Increasing the volume of osmotic media inc-reases the mass transfer rate. More solution volume could increase the rate of water loss and solid gain but it has some adverse effects also. Increasing the volume of solution causes an increase in operating costs. At the same time, solid gain is increased and the overall mass transfer could lower the product qua-lity by altering the taste of the product due to more migration of natural substances to the osmotic media. Therefore, the weight ratio of solution to sample

should be optimized. From the results, it was obs-erved that, increasing sample to solution ratio from 1:5 to 1:13 caused a major increase of WL, WR and SG which is due to an appreciable degree of dehyd-ration achieved by the contact of the fruit pieces with sufficient level of osmotic syrup to prevent dilution and resulted in steady water-solute transfer. Beyond 1:13 ratio, mass transfer properties of amla during osmotic dehydration had decreased and increased the operational cost of the process. This result is com-pliance with other researchers’ observations [32-34].

Quality characteristics

Rehydration ratio The effect of osmotic dehydration on rehydration

ratio increased linearly with the increase of the pro-cess variables (Figure 3a and b) up to sugar concen-tration of 45 °Brix, process time of 120 min, solution temperature of 45 °C and FL ratio of 1:12. This is due to the fact that the rehydration ratio is inversely rel-ated to the solute gain during osmotic dehydration process, which has to be leached out during rehyd-ration process.

Shrinkage The magnitude of the effect of process variables

is shown in Figure 3c and d, indicating a linear dec-rease in shrinkage with increase of osmotic solution temperature and concentration at 180 min of process duration. All the process parameters (except osmotic time and interaction of solution concentration and osmotic time) showed significant effect on the shrink-age of amla cubes statistically based on the p-value (Table 3). The increase in shrinkage with increase in temperature is that higher temperatures seem to pro-mote faster water loss through swelling and plastic-izing of cell membranes as well as the better water transfer characteristics on the product surface due to lower viscosity of the osmotic medium [35]. The rapid loss of water, especially in the beginning of OD, and the temperature of the osmotic solution account for a great proportion of shrinkage. Beyond that, decrease in shrinkage of the product with the advancement of process duration was observed, which may be due to the attainment of the saturated conditions. The solid gain, even in small amounts, can reinforce the strength of the solid material, creating more resist-ance to water removal and reduced shrinkage of the material.

Overall acceptability

Overall acceptability is useful to select the best quality of osmotically dehydrated product with maxi-mum consumer perception. The sensory attributes


556

Figure 3. Response surface plots for different quality parameters (RR: rehydration ratio, SH: shrinkage, OA: overall acceptability) during

osmotic dehydration of amla cubes in sugar solution.

are affected by different process variables and the results are shown in Figure 3. All the process para-meters (except osmotic time and interaction of sol-ution concentration and osmotic time) showed sig-nificant effect on the overall acceptability of amla cubes statistically based on the p-value (Table 3). The maximum acceptance was noticed for the pro-duct osmotically dehydrated under process condition

of temperature of 45 °C, concentration of 46 °Brix, FL ratio of 1:11.5 g/ml and time of 120 min. The overall acceptability is achieved due to the prevention of enzymatic and oxidative browning as the fruit pieces were surrounded by sugar and making it possible to retain good consumer observation. Similar results were observed in the osmotic dehydration of sweet anola flakes [36].


557

Optimization and validation of the optimized conditions

The second-order polynomial models obtained in this study were utilized for each response in order to determine the specified optimum conditions. These regression models are valid only in the selected expe-rimental domain. Therefore, the operating region was determined considering some economical, industrial and product quality-related constraints. In this study, sucrose concentration, FL ratio and immersion tem-perature were selected in the range of 30-50 °Brix, 1:5-1:15 g/ml and 30-50 °C. Considering the costs involved to increase the process time and also immer-sion time (X4) was not statistically significant for all responses in ANOVA table, the immersion time was fixed at 30 min. By applying the desired function methodology, the following optimized conditions were obtained: solution concentration of 43 °Brix, FL ratio of 1:10 g/ml, temperature of 30 °C and time of 30 min. At this optimum point, WR, SG, WL, RR, SH and OA found to be 27.5, 12.32, 32.68, 9.2, 7.3 and 7.16%, respectively.

Microstructure

The microstructural changes during osmotic dehydration are important in order to understand the changes that occurred in the compositional changes of fruits. Images of transversal cross-sections of treated and untreated samples are presented in Figure 4. Figure 4a shows the control sample of amla tissue, which did not receive any treatment other than the preparation for SEM. The bright regions in the micrograph are mainly the cytoplasmic membrane and the cell walls. The cells appeared torn and irre-gular in shape, with the presence of many empty

regions (regions which were not occupied by cells, Figure 4a).

Figure 4b shows that osmotic dehydration pro-cess (at optimal condition) changes the tissue struc-ture compared to the untreated sample. In fact, the cells appeared shrunk and distorted and their contour appeared irregular and wrinkling. This fact was pro-bably due to the solubilization of polysaccharides (cellulose, hemicellulose and pectin) that compose the cells walls, the water loss and the pre-concen-tration of sucrose on the surface of the tissue during the process [26,37-39]. Moreover, water loss induces the plasmolysis of cells and solid gain gives consist-ency to the tissues. There are several experimental findings in the literature that are consistent with our claims regarding the occurrence of cell structure modification during osmotic processing [38-40].

CONCLUSION

Box-Behnken response surface design was suc-cessfully employed in this study to evaluate and identify the optimal osmotic condition in order to pre-pare osmotically dehydrated amla cubes using sugar solution as an osmotic agent. From the experimental results, second order polynomial models were deve-loped for the responses (water loss, solid gain, weight reduction, rehydration ratio, shrinkage and overall acceptability). The results exhibited that osmotic sol-ution concentration, FL ratio and temperature have significant effects on the osmotic dehydration process of amla. The optimal conditions were found to be: sugar concentration of 50 °Brix, solution temperature of 30 °C, fruit to liquid ratio of 1:5 g/ml, and immersion time of 133 min.

Figure 4. SEM images of amla cubes a) raw and b) osmotically treated sample at optimal condition (sugar concentration of 50 °Brix,

solution temperature of 30 °C, fruit to liquid ratio of 1:5 g/ml and immersion time of 133 min).


558

Nomenclature

WR - Weight reduction WL - Water loss SG - Solid gain RR - Rehydration ratio SH - Shrinkage OA - Overall acceptability RSM - Response surface methodology BBD – Box–Behnken design °Brix – Degree Brix ANOVA - Analysis of variance SEM - Scanning electron microscopy FL ratio - Fruit to liquid ratio

REFERENCES

[1] S. Prakash, N. Jha Datta, J. Food Eng. 62 (2004) 305

[2] K.J. Park, A.Bin, F.P.R.Brod, J. Food Eng. 56 (2002) 97- -103

[3] A. Ispir, I. Togrul, Chem. Eng. Res. Des. 87 (2009) 166- -180

[4] N.K. Rastogi, K.S.M.S. Raghavarao, Food Biprod. Pro-cess. 82 (2004) 44-48

[5] A.L Raoult-Wack, Trends. Food Sci. Technol. 5 (1994) 255–260

[6] R. Moreira, A.M. Sereno, J. Food Eng. 57 (2003) 25-31

[7] F. Chenlo, R.Moreira, C.Fernandez-Herrer, G.Vazquez, J. Food Eng. 78 (2007) 765 – 774

[8] M.R. Ravindra, P.K. Chattopadhyay J. Food Eng. 44 (2000) 5–11

[9] S.P. Kumar, V.R. Sagar, J. Food Sci. Technol. 46 (2009) 259–262

[10] S. Yang, Y. Yang, W. Yang, Chin. J. App. Environ. Biol. 14 (2008) 846–854

[11] O.P. Chauhan, S. Srivastava, P. Pandey, G.K. Rao, Beverage Food World 32 (2005) 31-33

[12] P.R. Bhandari, M.A. Kamdod, Int. J. Green Pharm. 6 (2012) 257-269

[13] A.J. Al-Rehaily, T.A. Al-Howiriny, M.O.Al-Sohaibani, S. Rafatullah, Phytomed. 9 (2002) 515-522

[14] P.K. Pathak, D. Preeti, S. Kumar, J. Food Sci. Technol. 46 (2009) 283–285

[15] R.K. Goyal, R.T. Patil, A.R.P. Kingsly, W. Himanshu, K. Pradeep, Am. J. Food Technol. 3 (2008)13–23

[16] C.L. Kalra, Indian Food Packer. 42(4) (1988) 67–82

[17] AOAC, 17th ed., Association of Official Analytical Chem-istry, Rockville, MD, 2000

[18] G. Mazza, Int. J. Food Sci. Technol. 18 (1983) 113–123

[19] J.E. Lozano, E. Rotstein, M.J. Urbicain, J. Food Sci. 45 (1980) 1403-1407

[20] A.V.A. Resurreccion, Quantitative of quality attributes as perceived by the consumer. In Consumer sensory testing for product development, Aspen Publishers, New York, 1998

[21] J.P. Maran, V. Sivakumar, K. Thirugnanasambandham, R. Sridhar, J. Food Sci. Technol. 52 (2014) 3617-3626

[22] J. Prakash Maran, V. Sivakumar, R. Sridhar, V.P. Imma-nuel, Ind. Crop. Prod. 42 (2013) 159-168

[23] J.P. Maran, B. Priya, S. Manikandan, J. Food Sci. Tech-nol. 51 (2014) 1938-1946

[24] M.S. Rahman, J. Lamb, J. Food Sci. Technol. 27 (1990) 150-152

[25] H.N. Lazarides, E. Katsanidis, A. Nickolaides, J. Food Eng. 35 (1995) 151-166

[26] A.L. Raoult-Wack, S. Guilbert, M. Le Maguer, G. Rios. Drying Technnol. 9 (1991) 589–612

[27] D. Torreggiani, Food Res. Inter. 26 (1993) 59–68

[28] M. Shahabuddin, M.N.A. Hawader, S.M.D. Rahman, J. Food Process. Preser. 14 (1990) 375-391

[29] Z. Yao, M. Le Maguer, J. Food Eng. 29 (1996) 349-360

[30] K.J. Park, A. Bin, F.P.R. Brod, T.H.K.B. Park, J. Food Eng. 52 (2002) 293-298

[31] O.F. Kolawole, C.I. Joseph, A.A. Funke, J. Food Eng. 80 (2006) 979–985

[32] A. Askar, Y. Heikal, S. M. Ghonaim, M.G. Abdel-Fadeel, A.M. Ali, L.O. Abdel-Gaied, Fruit Processing. 7 (1996) 258-262

[33] S.M. Pokharkar, S. Prasad, H. Das, J. Food Sci. Technol. 34 (1997) 230–232

[34] H. Singh, J.Food Sci. Technol. 38 (2001) 152-154

[35] J.E. Contreras, T.G. Smryl, Can. Inst. Food Sci. Technol. J. 14 (1981) 310–314

[36] M.S. Alam, A. Singh, Int. J. Res. Rev. Appl. Sci, 3 (2010) 323-333

[37] D. Torreggiani, G. Bertolo, J. Food Eng. 49 (2001) 247– –253

[38] A. Delgado, A. Rubiolo, LWT-Food Sci. Technol. 38(2) (2005) 135–142

[39] P. Garcia, C. Mognetti, A. André-Bello, J. Martinez- -Monzo, J. Food Eng. 97 (2010) 154–160

[40] C. Nunes, C. Santos, G. Pinto, J.A. Lopes-da-silva, J.A. Saraiva, M.A. Coimbra, LWT-Food Sci. Technol. 41 (2008) 1776–1783.


559

D.TIROUTCHELVAME1

V. SIVAKUMAR2

J. PRAKASH MARAN3 1Department of Food Processing and

Engineering, Karunya University, Coimbatore, Tamil Nadu, India

2Department of Chemical Engineering, AC Tech Campus, Anna University,

Chennai, Tamil Nadu, India 3 Department of Food Technology,

Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India

NAUČNI RAD

KINETIKA PRENOSA MASE U OSMOTSKOJ DEHIDRATACIJI KOCKI INDIJSKOG OGROZDA (Emblica officinalis L.) U RASTVORU ŠEĆERA

Box-Behnken dizajn sa četiri faktora na tri nivo je korišćen za optimizacije uticaja različitih procesnih faktora (osmotska koncentracija, odnos voća i tečnosti, temperature i vreme dehidratacije) na karakteristike prenosa mase kao što su smanjenje mase, koli-čina rastvorka, gubitak vode, redehidratacioni odnos, smanjenje i ukupna asceptibilnost osmotski dehidratisanih kocki ogrozda. Kocke jednake veličine (10 mm×10 mm×10 mm) su potapane u šećerni rastvor različite koncentracije (30–50 °Brix) određeno vreme (30-–180 min) na različitim temperaturama (30-50 °C) i pri različitim odnosima voće-tečnost (1:5-1:15 g/ml). Rezultati pokazuju da procesni faktori imaju značajni uticaj na osmotsku dehidrataciju. Definisani su sledeći optimalni uslovi: koncentracija šećera od 50 °Brix, temperature rastvora 30 °C, odnos voće-tečnost 1:5 g/ml i vreme potapanja od 133 min. Praćene su takođe mikrokristalne promene za vreme osmotske dehidratacije koriš-ćenjem SEM metode.

Ključne reči: indijski ogrozd, osmotska dehidratacija, metodologija površine odziva, mikrostruktura.


CI&CEQ Vol. 21 Contents: Issues 1–4 YEAR 2015

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No. 1/I

Željka Kesić, Ivana Lukić, Miodrag Zdujić, Čedomir Jova-lekić, Hui Liu, Dejan Skala, Mechanochemical synthesis of CaO·ZnO.K2CO3 catalyst: Characterization and activity for methanolysis of sunflower oil ............................. 1

Sabina Kramar, Vilma Ducman, Mechanical and microstruc-tural characterization of geopolymer synthesized from low calcium fly ash ............................................................. 13

Odivan Zanella, Isabel Cristina Tessaro, Liliana Amaral Féris, Nitrate sorption on activated carbon modified with CaCl2: Equilibrium, isotherms and kinetics ........................ 23

N.M. Nikačević, L. Thielen, A. Twerda, P.M.J. Van den Hof, CFD analysis and flow model reduction for surfactant production in Helix reactor ................................................. 35

Linfeng Zhang, Jun Ji, Yuanxin Wu, Oxidative carbonylation of phenol to diphenyl carbonate by Pd/MFe2O4 magnetic catalyst ............................................................... 45

Vesna T. Tumbas Šaponjac, Gordana S. Ćetković, Slađana M. Stajčić, Jelena J. Vulić, Jasna M. Čanadanović-Brunet, Sonja M. Djilas, Optimization of the bioactive compounds content in raspberry during freeze-drying using response surface method ........................................ 53

Milovan Janićijević, Milesa Srećković, Branka Kaluđerović, Mirko Dinulović, Zoran Karastojković, Predrag Jovanić, Zorica Kovačević, Evaluation of laser beam interaction with carbon based material – glassy carbon ...................... 63

Đorđe B. Psodorov, Marijana M. Ačanski, Đura N. Vujić, Jovana S. Brkljača, Dragan Đ. Psodorov, Homogeneity of oil and sugar components of flour amaranth investigated by GC-MS...................................................... 71

R. Teflanab, S.M. Ghoreishi, J. Safdari, M. Torab-Mostaedi, Axial dispersion model in predictive mass transfer correlation for random pulsed packed column................... 77

Young Ho Kim, Dong Won Lee, Eun Ji Jung, Jun Tae Bae, Sang Gil Lee, Hyeong Bae Pyo, Kuk Hyoun Kang, Dong Kyu Lee, Preparation and characterization of quercetin-loaded silica microspheres stabilized by combined multiple emulsion and sol-gel processes ........................... 85

M. García-Dopico, A. García, Modelling fluidized catalytic cracking unit stripper efficiency ......................................... 95

Motasem N. Saidan, Improvement of linerboard com-pressive strength by hot-pressing and addition of recovered lignin from spent pulping liquor ....................... 107

Laishun Shi, Meijie Sun, Na Li, Bochen Zhang, A novel bet-aine type asphalt emulsifier synthesized and inves-tigated by online FTIR spectrophotometric method ......... 113

Qinghong You, Xiulian Yin, Hong Xu, Enhanced compound-enzymes--assisted extraction of polysaccharides from Cornus officinalis ............................................................. 123

Violeta D. Jakovljević, Jelica D. Stojanović, Miroslav M. Vrvić, The Potential application of fungus Trichoderma harzianum Rifai in biodegradation of detergent and industry ..................................................................... 131

No. 1/II

Ivana Jokić, Zoran Djurić, Katarina Radulović, Miloš Frant-lović, Fluctuations of the number of adsorbed micro/ /nanoparticles in sensors for measurement of particle concentration in air and liquid environments ................... 141

Renata Kovačević, Viša Tasić, Marija Živković, Nenad Živ-ković, Amelija Đorđević, Dragan Manojlović, Milena Jovašević-Stojanović, Mass concentrations and indoor-outdoor relationships of PM in selected educational buildings in Niš, Serbia .................................................... 149

Marija Živković, Milena Jovašević-Stojanović, Anka Cvet-ković, Ivan Lazović, Viša Tasić, Žana Stevanović, Ivan Gržetić, PAHs levels in gas and particle-bound phase in schools at different locations in Serbia ............................ 159

I. Deljanin, D. Antanasijević, M. Aničić Urošević, M. Toma-šević, Z. Sekulić, A. Perić-Grujić, M. Ristić, Selected trace element concentrations in ambient air and in horse chestnut leaves in Belgrade .................................. 169

Ivan Lazović, Milena Jovašević-Stojanović, Marija Živković, Viša Tasić, Žarko Stevanović, PM and CO2 variability and relationship in different school environments ........... 179

Z. Gršić, S. Pavlović, D. Arbutina, S. Dramlić, D. Dramlić, D. Nikezić, S. Dimović, J. Kaljević, M. Milinčić, Environ-mental impact assessment of the nuclear reactor in Vinča, based on the data on emission of radioactivity from the literature – A modeling approach ....................... 189

F. Hedayat, S. Stevanovic, B. Miljevic, S. Bottle, Z.D. Ris-tovski, Review – evaluating the molecular assays for measuring the oxidative potential of particulate matter ... 201

A. Cvetković, M. Jovašević-Stojanović, S. Matić-Besarabić, D.A. Marković, A.Bartoňová, Comparison of sources of urban ambient particle bound PAHs between non-heating seasons 2009 and 2012 in Belgrade, Serbia ...... 211

N. Castell, C. Guerreiro, B.R. Denby, A. González Ortiz, The role of air quality modelling in particulate matter management in cities. results from the air imple-mentation pilot ................................................................. 221

No. 2

Nazila Samimi Tehrani, Ghasem D. Najafpour, Mostafa Rahimnejad, Hossein Attar, Performance of upflow anaerobic sludge fixed film bioreactor for the treatment

CI&CEQ Vol. 21 Contents: issues 1–4 YEAR 2015

562

of high organic load and biogas production of cheese whey wastewater ............................................................. 229

Seyed Majid Ataei Ardestani, Morteza Sadeghi, Babak Beh-eshti, Saeid Minaei, Naser Hamdami, Vibro-fluidized bed heat pump drying of mint leaves with respect to phenolic content, antioxidant activity and color indices ... 239

Marija S. Petrović, Tatjana D. Šoštarić, Lato L. Pezo, Slavka M. Stanković, Časlav M. Lačnjevac, Jelena V. Milojko-vić, Mirjana D. Stojanović, Usefulness of ANN-based model for copper removal from aqueous solutions using agro industrial waste materials ........................................ 249

Bore V. Jegdić, Biljana M. Bobić, Miloš K. Pavlović, Ana B. Alil, Slaviša S. Putić, Stress corrosion cracking resist-ance of aluminum alloy 7000 series after two-step aging ................................................................................ 261

Aleksandra Petrovič, Marjana Simonič, The efficiency of a membrane bioreactor in drinking water denitrification ..... 269

Dragutin M. Nedeljković, Marija P. Stevanović, Mirko Z. Stijepović, Aleksandar P. Stajčić, Aleksandar S. Grujić, Jasna T. Stajić-Trošić, Jasmina S. Stevanović, The pos-sibility of application of zeolyte powders for the construction of membranes for carbon dioxide separ-ation ................................................................................. 277

Veselinka Grudić, Jelena Šćepanović, Ivana Bošković, Removal of cadmium (II) from aqueous solution using fermented grape marc as a new adsorbent ..................... 285

Amal Juma Habish, Slavica Lazarević, Ivona Janković-Čas-tvan, Branislav Potkonjak, Đorđe Janaćković, Rada Pet-rović, The effect of salinity on the sorption of cadmium ions from aqueous medium on Fe(III)-sepiolite ............... 295

Shaopeng Guo, Lina Lv, Jia Zhang, Xin Chen, Ming Tong, Wanzhong Kang, Yanbo Zhou, Jun Lu, Simultaneous removal of SO2 and NOx with ammonia combined with gas-phase oxidation of NO using ozone .......................... 305

Jau-Kai Wang, Jir-Ming Char, Optimization study on hard-ness of gold film through supercritical electroplating process by response surface methodology ..................... 311

Lawrence Koech, Ray Everson, Hein Neomagus, Hilary Rutto, Dissolution kinetics of south african coal fly ash and the development of a semi-empirical model to predict dissolution ............................................................ 319

Zhuoni Hou, Xianrui Liang, Feng Su, Weike Su, Preparative isolation and purification of seven compounds from Hibiscus mutabilis L. leaves by two-step high-speed counter-current chromatography ..................................... 331

Ruifang Zhao, Yulong Wang, Yonghui Bai, Yongfei Zuo, Lunjing Yan, Fan Li, Effects of fluxing agents on gasi-fication reactivity and gas composition of high ash fusion temperature coal ................................................... 343

Veselinka V. Grudić, Nada Z. Blagojević, Vesna L. Vukaši-nović-Pešić, Snežana R. Brašanac, Kinetics of degrad-ation of ascorbic acid by cyclic voltammetry method ....... 351

Ahmet Ozan Gezerman, Burcu Didem Çorbacıoğlu, Effects of sodium silicate, calcium carbonate and silicic acid on ammonium nitrate degradation and analytical invest-igations of the degradation process on an industrial scale ................................................................................ 359

No. 3

Nenad D. Nikolić, Đorđe P. Medarević, Jelena D. Đuriš, Dragana D. Vasiljević, Comparison of drug release and mechanical properties of tramadol hydrochloride matrix tablets prepared with selected hydrophilic polymers ....... 369

Saeid Shokri, Mohammad Taghi Sadeghi, Mahdi Ahmadi Marvast, Shankar Narasimhan, Saeid Minaei, Naser Hamdami, Integrating principal component analysis and vector quantization with support vector regression for sulfur content prediction in hydrodesulfurization process ............................................................................ 379

Mile Veljovic, Sasa Despotovic, Milan Stojanovic, Sonja Pecic, Predrag Vukosavljevic, Miona Belovic, Ida Les-kosek-Cukalovic, The fermentation kinetics and phys-icochemical properties of special beer with addition of Prokupac grape variety .................................................... 391

Najmi Ahmed Essawet, Dragoljub Cvetković, Aleksandra Velićanski, Jasna Čanadanović-Brunet, Jelena Vulić, Vuk Maksimović, Siniša Markov, Polyphenols and anti-oxidant activities of Kombucha beverage enriched with Coffeeberry® extract ........................................................ 399

Nataša S. Tomović, Kata T. Trifković, Marko P. Rakin, Marica B. Rakin, Branko M. Bugarski, Influence of com-pression speed and deformation percentage on mechanical properties of calcium alginate particles ........ 411

Radojica Pešić, Tatjana Kaluđerović Radoičić, Nevenka Bošković-Vragolović, Zorana Arsenijević, Željko Grbavčić, Pressure drop in packed beds of spherical particles at ambient and elevated air temperatures ......... 419

Marija A. Ilić, Franz-Hubert Haegel, Vesna M. Pavelkić, Snezana J. Zlatanović, Zoran S. Marković, Aleksandar S. Cvjetić, Unusually sluggish microemulsion system with water, toluene and a technical branched alkyl poly-ethoxylate ........................................................................ 429

Shifeng Li, Yanming Shen, Dongbing Liu, Lihui Fan, Zhe Tan, Zhigang Zhang, Wenxiu Li, Wenpeng Li, Experi-mental study of concentration of tomato juice by CO2 hydrate formation ............................................................. 441

Aleksandar R. Mladenović, Milka B. Jadranin, Aleksandar D. Pavlović, Slobodan D. Petrović, Saša Ž. Drmanić, Milka L. Avramov Ivić, Dušan Ž. Mijin, Liquid chroma-tography and liquid chromatography-mass spectrometry analysis of donepezil degradation products .................... 447

Jiajia Dai, Benfang H. Ruan, Ying Zhu, Xianrui Liang, Feng Su, Weike Su, Preparation of nanosized fluticasone propionate nasal spray with improved stability and uniformity ......................................................................... 457

No. 4

Jun Tan, Xiaoyan Wei, Yuxia Ouyang, Rui Liu, Ping Sun, Juhong Fan, Evaluation of insoluble xanthate and crosslinked starch-graft-polyacrylamide-co-sodium xanthate for the adsorption of Cu(II) in aqueous solutions .......................................................................... 465

Ogbemudia Joseph Ogbebor, Felix Ebhodaghe Okieimen, David Ehioghilen Ogbeifun, Uzoma Ndubuisi Okwu, Organomodified kaolin as filler for natural rubber............ 477

Vesna M. Pavelkić, Tanja P. Brdarić, Marija P. Petrović, Gavrilo M. Šekularac, Milica G. Košević, Lato L. Pezo,

CI&CEQ Vol. 21 Content: issues 1–4 YEAR 2015

563

Marija A. Ilić, Application of Peleg model on mass transfer kinetics during osmotic dehydratation of pear cubes in sucrose solution ................................................ 485

Rongyan Shen, Fang Liu, Te Li, Xia Xu, Yuting Liang, Xing-qing Zhao, Wenyi Zhang, Treatment of 2-diazo-4,6- -dinitrophenol wastewater using TiO2/SiO2 composite film in a photocatalytic reactor ......................................... 493

Milutin M. Milosavljević, Ivan M. Vukićević, Veis Šerifi, Jas-mina S. Markovski, Ivana Stojiljković, Dušan Ž. Mijin, Aleksandar D. Marinković, Optimization of the synthesis of N-alkyl and N,N-dialkyl thioureas from waste water containing ammonium thiocyanate .................................. 501

Sheng Fang, Li-Ping Wang, Ting Wu, Mathematical model-ing and effect of blanching pretreatment on the drying kinetics of Chinese Yam (Dioscorea opposita) ................ 511

Zorana Arsenijević, Tatjana Kaluđerović Radoičić, Mihal Đuriš, Željko Grbavčić, Experimental investigation of heat transfer in three-phase fluidized bed cooling column ............................................................................. 519

Vesna S. Cvetković, Luka J. Bjelica, Nataša M. Vukićević, Jovan N. Jovićević, Alloy formation by Mg under-potential deposition on Al from nitrate melts .................... 527

Rajamohan Natarajan, Jamila Al-Sinani, Saravanan Viswa-nathan, Performance evaluation and kinetic studies on removal of benzene in up-flow tree bark based biofilter .. 537

D. Tiroutchelvame, V. Sivakumar, J. Prakash Maran, Mass transfer kinetics during osmotic dehydration of Amla (Emblica officinalis L.) cubes in sugar solution ................ 547

Contents: Vol. 21, Issues 1–4, 2015 ....................................... 561

Author Index, Vol. 21, 2015 .................................................... 565

Journal of the Association of Chemical Engineers, Belgrade, Serbia

CI&CEQ Vol. 21 Author Index YEAR 2015

565

A Ačanski M. Marijana (1/I) 71 Al-Sinani Jamila (4) 537 Alil B. Ana (2) 261 Amal Juma Habish (2) 295 Aničić Urošević M. (1/II) 169 Antanasijević D. (1/II) 169 Arbutina D. (1/II) 189 Arsenijević Zorana (3) 419, (4) 519 Avramov Ivić L. Milka (3) 447 B Babak Beheshti (2) 239 Bartonova A. (1/II) 211 Belović Miona (3) 391 Benfang H. Ruan (3) 457 Bjelica J. Luka (4) 527 Blagojević Z. Nada (2) 351 Bobić M. Biljana (2) 261 Bošković Ivana (2) 285 Bošković-Vragolović Nevenka (3) 419 Bottle S. (1/II) 201 Brašanac R. Snežana (2) 351 Brdarić P. Tanja (4) 485 Brkljača S. Jovana (1/I) 71 Bugarski M. Branko (3) 411 C Castell N. (1/II) 221 Char Jir-Ming (2) 311 Corbacioglu Didem Burcu (2) 359 Cvetković Anka (1/II) 159, 211 Cvetković Dragoljub (3) 399 Cvetković S. Vesna (4) 527 Cvjetić S. Aleksandar (3) 429

Ć Ćetković S. Gordana (1/I) 53 Č Čanadanović-Brunet M. Jasna (1/I) 53; (3) 399 D Dai Jiajia (3) 457 Deljanin I. (1/II) 169 Denby B.R. (1/II) 221 Despotović Saša (3) 391 Dimović S. (1/II) 189 Dinulović Mirko (1/I) 63 Dramlić D. (1/II) 189 Dramliić S. (1/II) 189 Drmanić Ž. Saša (3) 447 Ducman Vilma (1/I) 13 Dj Djilas M. Sonja (1/I) 53 Djordjević Amelija (1/II) 149 Djurić Zoran (1/II) 141 Djuriš D. Jelena (3) 369 Djuriš Mihal (4) 519 F Feng Su (2) 331; (3) 457 Feris Amaral Liliana (1/I) 23 Frantlović Miloš (1/II) 141 G Garcia A. (1/I) 95 Garcia-Dopico M. (1/I) 95


566

Gezerman Ahmet Ozan (2) 359 Ghasem D. Najafpour (2) 229 Ghoreishi S.M. (1/I) 77 Gonzalez Ortiz A. (1/II) 221 Grbavčić Željko (3) 419, (4) 519 Gršić Z. (1/II) 189 Grudić V. Veselinka (2) 285, 351 Grujić S. Aleksandar (2) 277 Gržetić Ivan (1/II) 159 Guerreiro C. (1/II) 221 Guo Shaopeng (2) 305 H Haegel Franz-Hubert (3) 429 Hedayat F. (1/II) 201 Hein Neomagus (2) 319 Hong Xu (1/I) 123 Hossein Attar (2) 229 Hui Liu (1/I) 1 Hyeong Bae Pyo (1/I) 85 I Ilić A. Marija (3) 429; (4) 485 J Jadranin B. Milka (3) 447 Jakovljević D. Violeta (1/I) 131 Janaćković Djordje (2) 295 Janićijević Milovan (1/I) 63 Janković-Častvan Ivona (2) 295 Jegdić V. Bore (2) 261 Jokić Ivana (1/II) 141 Jovalekić Čedomir (1/I) 1 Jovanić Predrag (1/I) 63 Jovašević-Stojanović Milena (1/II) 149, 159, 179, 211 Jovićević N. Jovan (4) 527 Juhong Fan (4) 465 Jun Ji (1/I) 45 Jun Lu (2) 305 Jun Tae Bae (1/I) 85 Jun Tan (4) 465

Jung Ji Eun (1/I) 85 K Kaljević J. (1/II) 189 Kaludjerović Branka (1/I) 63 Kaludjerović Radoičić Tatjana (3) 419, (4) 519 Kang Wanzhong (2) 305 Karastojković Zoran (1/I) 63 Kesić Željka (1/I) 1 Koech Lawrence (2) 319 Košević G. Milica (4) 485 Kovačević Renata (1/II) 149 Kovačević Zorica (1/I) 63 Kramar Sabina (1/I) 13 Kuk Hyoun Kang (1/I) 85 L L.Thielen (1/I) 35 Lačnjevac M. Časlav (2) 249 Lazarević Slavica (2) 295 Lazović Ivan (1/II) 159, 179 Lee Kyu Dong (1/I) 85 Dong Won Lee (1/I) 85 Leskošek-Čukalović Ida (3) 391 Li Fan (2) 343 Li Shifeng (3) 441 Li Wenpeng (3) 441 Li Wenxiu (3) 441 Liu Fang (4) 493 Liu Dongbing (3) 441 Lihui Fan (3) 441 Lukić Ivana (1/I) 1 Lv Lina (2) 305 M Mahdi Ahmadi Marvast (3) 379 Maksimović Vuk (3) 399 Manojlović Dragan (1/II) 149 Maran Prakash J. (4) 547 Marinković D. Aleksandar (4) 501 Markov Siniša (3) 399 Marković A.D. (1/II) 211


567

Marković S. Zoran (3) 429 Markovski S. Jasmina (4) 501 Matić-Besarabić S. (1/II) 211 Medarević P. Djordje (3) 369 Meijie Sun (1/I) 113 Mijin Ž. Dušan (3) 447, (4) 501 Milinčić M. (1/II) 189 Miljević B. (1/II) 201 Milojković V. Jelena (2) 249 Milosavljević M. Milutin (4) 501 Ming Tong (2) 305 Mladenović R. Aleksandar (3) 447 Mohammad Taghi Sadeghi (3) 379 Morteza Sadeghi (2) 239 Mostafa Rahimnejad (2) 229 Motasem N. Saidan (1/I) 107 N Na Li (1/I) 113 Najmi Ahmed Essawet (3) 399 Naser Hamdami (2) 239; (3) 379 Nazila Samimi Tehrani (2) 229 Nedeljković M. Dragutin (2) 277 Nikačević M. Nikola (1/I) 35 Nikezić D. (1/II) 189 Nikolić D. Nenad (3) 369 O Odivan Zanella (1/I) 23 Ogbebor Joseph Ogbemudia (4) 477 Ogbeifun Ehioghilen David (4) 477 Okieimen Ebhodaghe Felix (4) 477 Okwu Ndubuisi Uzoma (4) 477 P Pavelkić M. Vesna (3) 429; (4) 485 Pavlović D. Aleksandar (3) 447 Pavlović K. Miloš (2) 261 Pavlović S. (1/II) 189 Pecić Sonja (3) 391 Perić-Grujić A. (1/II) 169 Pešić Radojica (3) 419 Petrovič Aleksandra (2) 269

Petrović D. Slobodan (3) 447 Petrović P. Marija (4) 485 Petrović Rada (2) 295 Petrović S. Marija (2) 249 Pezo L. Lato (2) 249; (4) 485 Ping Sun (4) 465 Potkonjak Branislav (2) 295 Psodorov B. Djordje (1/I) 71 Psodorov Dj. Dragan (1/I) 71 Putić S. Slaviša (2) 261 R Radulović Katarina (1/II) 141 Rajamohan Natarajan (4) 537 Rakin B. Marica (3) 411 Rakin P. Marko (3) 411 Ray Everson (2) 319 Ristić M. (1/II) 169 Ristovski D.Z. (1/II) 201 Rongyan Shen (4) 493 Rui Liu (4) 465 Rutto Hilary (2) 319 S Saeid Minaei (2) 239; (3) 379 Saeid Shokri (3) 379 Safdari J. (1/I) 77 Sang Gil Lee (1/I) 85 Saravanan Viswanathan (4) 537 Sekulić Z. (1/II) 169 Seyed Majid Ataei Ardestani (2) 239 Shankar Narasimhan (3) 379 Sheng Fang (4) 511 Shi Laishun (1/I) 113 Simonič Marjana (2) 269 Sivakumar V. (4) 547 Skala Dejan (1/I) 1 Srećković Milesa (1/I) 63 Stajčić M. Sladjana (1/I) 53 Stajčić P. Aleksandar (2) 277 Stajić-Trošić T. Jasna (2) 277 Stanković M. Slavka (2) 249 Stevanović P. Marija (2) 277 Stevanović S. (1/II) 201


568

Stevanović S. Jasmina (2) 277 Stevanović Žana (1/II) 159 Stevanović Žarko (1/II) 179 Stijepović Z. Mirko (2) 277 Stojanović D. Jelica (1/I) 131 Stojanović D. Mirjana (2) 249 Stojanović Milan (3) 391 Stojiljković Ivana (4) 501 Š Šćepanović Jelena (2) 285 Šekularac M. Gavrilo (4) 485 Šerifi Veis (4) 501 Šoštarić D. Tatjana (2) 249 T Tasić Viša (1/II) 149, 159, 179 Te Li (4) 493 Teflanab R. (1/I) 77 Tessaro Cristina Isabel (1/I) 23 Ting Wu (4) 511 Tiroutchelvame D. (4) 547 Tomašević M. (1/II) 169 Tomović S. Nataša (3) 411 Torab-Mostaedi M. (1/I) 77 Trifković T. Kata (3) 411 Tumbas Šaponjac T. Vesna (1/I) 53 Twerda A. (1/I) 35 V Van den Hof P.M.J. (1/I) 35 Vasiljević D. Dragana (3) 369 Velićanski Aleksandra (3) 399 Veljović Mile (3) 391 Vrvić M. Miroslav (1/I) 131 Vujić N. Djura (1/I) 71 Vukašinović-Pešić L. Vesna (2) 351 Vukićević M. Ivan (4) 501 Vukićević M. Nataša (4) 527 Vukosavljević Predrag (3) 391 Vulić J. Jelena (1/I) 53; (3) 399

W Wang Jau-Kai (2) 311 Li-Ping Wang (4) 511 Wei Xiaoyan (4) 465 Weike Su (2) 331; (3) 457 X Xia Xu (4) 493 Xianrui Liang (2) 331; (3) 457 Xin Chen (2) 305 Y Yanbo Zhou (2) 305 Yan Lunjing (2) 343 Yanming Shen (3) 441 Yin Xiulian (1/I) 123 Ying Zhu (3) 457 Yongfei Zuo (2) 343 Yonghui Bai (2) 343 Young Ho Kim (1/I) 85 Yuanxin Wu (1/I) 45 Yulong Wang (2) 343 Yuting Liang (4) 493 Yuxia Ouyang (4) 465 Z Zdujić Miodrag (1/I) 1 Zhang Bochen (1/I) 113 Zhang Jia (2) 305 Zhang Linfeng (1/I) 45 Zhao Ruifang (2) 343 Zhao Xingqing (4) 493 Zhang Wenyi (4) 493 Zhe Tan (3) 441 Zhigang Zhang (3) 441 Zhuoni Hou (2) 331 Zlatanović J. Snezana (3) 429 Ž Živković Marija (1/II) 149, 159, 179 Živković Nenad (1/II) 149

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