production and characterization of porous carbon from date palm seeds by chemical activation with h...
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PRODUCTION AND CHARACTERIZATIONOF POROUS CARBON FROM DATE PALMSEEDS BY CHEMICAL ACTIVATION WITHH3PO4: PROCESS OPTIMIZATION FORMAXIMIZING ADSORPTION OF METHYLENEBLUESuresh Kumar Reddy Kuppireddy a , Kashif Rashid a , Ahmed AlShoaibi a & Chandrasekar Srinivasakannan aa Chemical Engineering Department , The Petroleum Institute , AbuDhabi , United Arab EmiratesAccepted author version posted online: 12 Nov 2013.Publishedonline: 28 Apr 2014.
To cite this article: Suresh Kumar Reddy Kuppireddy , Kashif Rashid , Ahmed Al Shoaibi &Chandrasekar Srinivasakannan (2014) PRODUCTION AND CHARACTERIZATION OF POROUS CARBONFROM DATE PALM SEEDS BY CHEMICAL ACTIVATION WITH H3PO4: PROCESS OPTIMIZATION FORMAXIMIZING ADSORPTION OF METHYLENE BLUE, Chemical Engineering Communications, 201:8,1021-1040, DOI: 10.1080/00986445.2013.797896
To link to this article: http://dx.doi.org/10.1080/00986445.2013.797896
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Production and Characterization of Porous Carbonfrom Date Palm Seeds by Chemical Activation with
H3PO4: Process Optimization for MaximizingAdsorption of Methylene Blue
SURESH KUMAR REDDY KUPPIREDDY,KASHIF RASHID, AHMED AL SHOAIBI, ANDCHANDRASEKAR SRINIVASAKANNAN
Chemical Engineering Department, The Petroleum Institute, Abu Dhabi,United Arab Emirates
The potential of date palm pits to be a suitable precursor for preparation of porouscarbon was explored in the present work, utilizing phosphoric acid as the activatingagent. Experimental methods reported in the literature were chosen with certainmodifications in order to simplify the process. Process optimization was performedusing the popular response surface methodology (RSM) adopting a Box-Behnkendesign. Process optimization was intended to maximize the porous carbon yieldand the methylene blue (MB) adsorption capacity, with the process variables beingthe activation temperature, impregnation ratio (IR), and activation time. Thestructural characteristics were assessed based on nitrogen adsorption isotherms,SEM, and FT-IR, while the adsorption capacity was estimated using MB adsorp-tion. The optimized experimental conditions were identified to be an activationtemperature of 400�C, IR of 3, and activation time of 58min, with the resultant porouscarbon having a yield of 44% andMB adsorption capacity of 345mg=g. The structuralcharacteristics of the porous carbon reveal the BET surface area to be 725m2=g, withpore volume of 1.26 cc=g, an average pore diameter of 2.91 nm, and total microporevolume of 0.391 cc=g. The popular Langmuir and Freundlich adsorption isothermmodels were tested, and a maximum monolayer adsorption capacity of MB was esti-mated to be 455mg=g, which compares with the highest for MB reported in literature,evidencing the suitability of porous carbon for adsorption of macromolecularcompounds. The low activation temperature and activation time with highest yieldrender the process technically and economically attractive for commercial use.
Keywords Adsorption isotherms; BET surface area; Methylene blue; Porouscarbon; RSM
Introduction
Porous carbon in its broadest sense is a term that includes a wide range ofamorphous carbonaceous materials that exhibit a high degree of porosity and an
Address correspondence to Suresh Kumar Reddy Kuppireddy, Chemical EngineeringDepartment, The Petroleum Institute, P.O. Box 2533, AbuDhabi, UAE. E-mail: [email protected]
Color versions of one or more of the figures in the article can be found online atwww.tandfonline.com/gcec.
Chem. Eng. Comm., 201:1021–1040, 2014Copyright # Taylor & Francis Group, LLCISSN: 0098-6445 print=1563-5201 onlineDOI: 10.1080/00986445.2013.797896
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extended intra-particulate surface area. They are prepared using thermal decompo-sition of a variety of carbonaceous substances, usually from charcoal due to its lowcost and availability (Ahmadpour and Do, 1996; Bansal and Goyal, 2005). It has largenumber of applications in liquid and gas phase adsorption processes, for removal ofimpurities in drinking=wastewater systems for reduction of organic pollutants, andas a catalyst support in a variety of chemical syntheses, e.g., vinyl chloride synthesis(Gurrath et al., 2000; Mazyck and Cannon, 2000; Walker and Weatherley, 1998).
The physical properties and the chemical composition of the precursor, as wellas the methods and process conditions employed for activation, determine theyield, surface area, pore size distribution, surface functional groups, and adsorptionproperties of the porous carbon (Laszlo et al., 1997). The adsorption capacity ofporous carbons are determined by their porous structure, but is strongly influencedby the chemical nature (Bansal and Goyal, 2005). Any material that is carbonaceousand lignocellulosic in nature can be utilized as a precursor for the preparation ofporous carbon. The two major methods of preparation of porous carbon are cate-gorized as physical and chemical activation. Physical activation is a two-stage pro-cess in which precursors are carbonized in inert atmosphere prior to activationwith either steam or CO2 or a combination of both.
Generally, chemical activation is a single-stage process, with the activating agentsbeing phosphoric acid, nitric acid, zinc chloride, K2CO3, and bases such NaOH andKOH. Chemical activation slows down the formation of tar during thermal degra-dation of lignocellulosic material (Caturla et al., 1991) in the presence of a dehydrat-ing agent. It has been well documented that the activation temperatures are low whilethe yield of porous carbon is high in the chemical activation process as compared tophysical activation (Lim et al., 2010). Phosphoric acid and zinc chloride have beenused extensively in the chemical activation process for biomass-based precursors,while KOH is utilized for coal-based precursors (Puziy et al., 2002). The chemical acti-vation agents first degrade the cellulosic material, and the process of carbonizationcreates suitable pore structure as a result of dehydration (Azevedo et al., 2007).
Phosphoric acid is preferred as compared to zinc chloride due to its nonpollutingnature and is widely used in pharmaceutical and food industries. In addition, phos-phoric acid can be easily recovered by simply washing with water and can be reusedin the process, rendering it economically viable (Diao et al., 2002; Rodrıguez-Reinoso et al., 1995; Srinivasakannan and Zailani Abu Bakar, 2004; Teng et al.,1998). Phosphoric acid imparts cation-exchange capacity, making it chemicallystable in both acidic and base media in addition to its thermal stability (Puziyet al., 2002). Utilization of phosphoric acid as a suitable activating agent for prep-aration of activated carbon (AC) from a variety of agricultural wastes has been wellrecorded in the literature (Al-Qaessi and Abu-Farah, 2010; Attia et al., 2008; Fierroet al., 2010; Girgis and El-Hendawy, 2002; Guo and Rockstraw, 2007; Haimour andEmeish, 2006; Prahas et al., 2008; Zuo et al., 2005). However, it should be noted thatthe activation methods are different, as the majority of the articles report single-stageactivation with activation in inert conditions. The benefits of two-stage activation inthe absence of inert media have been highlighted from the commercial productionpoint of view as well as with respect to the quality of carbon (Lim et al., 2010).The authors also highlighted the ability of the process to generate high-surface-areamesoporous carbon with a mean pore diameter of 3.2 nm.
Agricultural wastes are considered to be a very important feedstock as they arerenewable as well as low-cost materials (Stavropoulos and Zabaniotou, 2005). Date
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seeds are among such wastes and very few authors have reported utilization ofdate seeds as a precursor for the preparation of porous carbon (Banat et al., 2003;El-Naas et al., 2010a, 2010b; Haimour and Emeish, 2006; Hameed et al., 2009).Dates are abundantly available in the United Arab Emirates (UAE), and theirannual production capacity was reported to be 765000 MT in 2003, which consti-tutes 11% of the global production. Date seeds have a compact cellular structureand comparatively low porosity (Girgis and El-Hendawy, 2002). The chemical com-position of date seed is reported to constitute hemicellulose (23%), lignin (15%),cellulose (57%), and ash (5%) (Haimour and Emeish, 2006).
Effluents from dyeing processes in the textile industries are known to contain colordye, heavy metals, and surfactants that are stable to photodegradation, biodegrada-tion, and oxidizing agents (Garg et al., 2004; Kannan and Sundaram, 2001; Maliket al., 2007). There has been great concern to remove synthetic dyes from wastewateras they (or their degradation components) may be carcinogens and toxins that requirean effective treatment system. Conventional methods, including precipitation, ionexchange, membrane filtration, and reverse osmosis, have been applied for the removalof pollutants from wastewaters. However, these processes involve high investment andare energy intensive (Demiral et al., 2008). The ever-evolving and fast-changing situ-ation demands waste management mechanisms that are effective and economical.Adsorbents with large surface areas and appropriate pore size that can adsorb largequantities of dye molecules can potentially be a part of the integrated waste manage-ment system to meet stringent environmental regulations (Chan et al., 2008).
The present work is aimed at investigating the following:
i. The utilization of a two-stage process (Lim et al., 2010) with semi-carbonization at170�C, followed by activation at desired conditions. However, Lim and coworkerspre-dried the impregnated mixture at 100�C to ensure complete soaking of acidbefore semi-carbonization. The present work attempts to combine the pre-dryingand semi-carbonization stage as a single operation by prolonging the pre-dryingstage until the mixture is bone dry, suitable for direct carbonization (second stageof activation), utilizing a self-generated atmosphere (SGA). The action of phos-phoric acid on lignocellulosic material to cause chemical and structural changesat temperatures starting as low as 50�C is known (Zhang et al., 2009), however,the corresponding rates are low. Physically this involves reconfiguration of themolecules resulting in formation of a pasty mass (polymerization) followed bydepolymerization, resulting in dry material. The higher yield of porous carbonusing phosphoric acid has been attributed to the reconfiguration of the lignocellu-losic material into a larger stable structural unit that controls the release of volatilematter (Girgis and El-Hendawy, 2002; Nakagawa et al., 2007).
ii. Process optimization of the process variables, activation temperature, activationtime, and impregnation ratio (IR) on the yield and methylene blue (MB) adsorp-tion capacity using response surface methodology (RSM) with the Box-Behnkenmethod (BBM). The objective functions for optimization are maximization ofyield and MB adsorption capacity. MB was chosen as the adsorbate, since it isa larger molecule with a molecular diameter of 0.8 nm and is accessible to poresthat are larger than 1.3 nm (Valdes et al., 2002).
iii. Assess the structural characteristics of porous carbon to estimate the BET sur-face area, pore volume, and mean pore diameter using nitrogen adsorption iso-therms, the surface functional group using Fourier transform-infrared (FT-IR)
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spectroscopy, and the surface morphology using scanning electron microscopy(SEM) and assess the effect of adsorption temperature and pH on the equilib-rium adsorption isotherm of MB.
Experimental Methods
Materials and Methods
Raw date seeds from the date processing industry inUAEwas utilized as the precursor.They were first washed in 0.1M H2SO4 (95–97% purity) to remove dirt and greasymaterial on the seed surface, followed by repeated washing with distilled water toensure all the impurities as well as the acid were removed. The seeds were dried inan air oven at 105�C for 2 h. After drying, the seeds were crushed using a PanasonicMX-AC210S mixer grinder. A 15-g amount of crushed date seeds of size 200 to 400microns was taken as the precursor and mixed with H3PO4 (98% purity) of 60% con-centration, at a desired impregnation ratio (IR) (range 2–4). IR is defined as grams of100% phosphoric acid=grams of bone dry precursor. The mixture was stirred for 5 h toensure complete soaking of the precursor in phosphoric acid. After ensuring completesoaking of acid into the precursor, the mixture was dried in an air oven at 105�C until itwas completely dry and crisp. The dried powdery material was carbonized at a tem-perature ranging from 400� to 500�C in the activation time range of 45 to 75min, ina SGA. Upon completion of the experiment, the carbonized samples were cooled toroom temperature. The samples were washed repeatedly in batches, with a minimumof 10 washes to ensure all the salts of phosphoric acid were removed from the activatedsample. This was ensured with the conductivity of filtrate lower than 50 ms. The washedproduct was then dried in an air oven at 105�C for 12h to ensure complete dryness. Theyield of porous carbon was estimated based on the grams of bone dry porous carbonprepared to the grams of bone dry date palm seeds utilized for activation.
MB was supplied by Sigma Aldrich, and distilled water was used for thepreparation of stock solutions with concentrations of 1200, 800, and 400mg=L MBsolution. A UV spectrophotometer was utilized at a wavelength of 600 nm to esti-mate the concentration of the MB solution before and after adsorption.
Adsorption Isotherms
Equilibrium batch adsorption experiments were conducted using Erlenmeyer flasksof 250mL capacity. A fixed amount (0.1 g) of adsorbent was taken in each flaskand a known concentration of MB (400, 800, and 1200mg=L) was added to eachflask. The bottles were kept in a shaker water bath at different temperatures (30�,40�, and 50�C) at 200 rpm. The experiments were continued at stable conditions fora period of 35 h to ensure equilibrium between the solid (adsorbent) and the liquidphase (adsorbate). The effect of pH was assessed by adjusting the pH of the liquidphase with either 0.1M NaOH or concentrated HCl to the desired pH. The pH ofsolution of the virgin MB solution was found to be 3.7 after adding porous carboninto the solution. The effect of pH was assessed at the liquid bath temperature of30�C at an initial concentration of MB of 800mg=L.
The amount of MB adsorbed by the adsorbent was calculated using the formula
qðeÞ ¼ ðCo � CeÞVW
ð1Þ
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where q(e) is the equilibrium adsorption (mg=g), Co is the initial concentration ofMB solution (mg=L), Ce is the equilibrium concentration (mg=L), V is the volumeof MB solution taken for the adsorption experiment (L), and W is the weight ofadsorbent (g).
Structural Characteristics
Infrared (IR) spectroscopy is one of the classical techniques used routinely to deriveinformation regarding the nature of phases, types of metal-ligand bonding, and thepresence of different functional groups. FT-IR spectra of samples were recorded on aBio-Rad 175c instrument at ambient conditions using KBr as the diluent to estimatethe functional groups present in the AC. The samples were loaded into the sampleholder and scanned in the mid IR region, 100 to 4000 cm�1. A pellet made of nearlythe same amount of KBr was used as the background. The resolution selected was4 cm�1 and total of 32 scans were made.
The samples were analyzed at �196�C with an accelerated surface area andporosimetry system (Autosorb-1-C, Quantachrome). Prior to gas adsorption mea-surements, the carbon was degassed at 300�C in a vacuum condition for a periodof at least 2 h. The nitrogen adsorption isotherm was measured over a relativepressure (P=P0) range from approximately 10�7 to 1. The BET surface area wascalculated from the isotherms by using the Brunauer-Emmett-Teller (BET) equation.The Dubinin-Radushkevich (DR) method was used to calculate the microporevolume. The total pore volume was calculated from nitrogen adsorption data asthe volume of liquid nitrogen at a relative pressure of approximately 0.99 to 1(Lyubchik et al., 2002).
A FEG-250 SEM instrument (FEI, Holland) was employed at an accumulationvoltage of 30KV with 2.5K magnification to estimate the surface pore structure ofthe porous carbon.
Experimental Design
RSM using a Box-Behnken experimental design is a standard statistical tool widelyused for process optimization with minimum number of experiments (Gonen andAksu, 2008). The process variables were the activation temperature (X1), IR (X2),and activation time (X3), while the response variables were the yield (Y1) and MB(Y2). The Box-Behnken design recommends a minimum number of 15 experiments,including the three repeat runs, for optimizing the process parameters. The upperand lower limits of the variables are provided in Table I, where ‘‘�1’’ representsthe low level, ‘‘þ1’’ the high level, and ‘‘0’’ the center point. Table II shows theexperimental conditions for which the experiments were conducted along with theresults. The upper and lower limits were fixed based on extensive literature analysis
Table I. High and low levels of factors
Factor Low level (�1) Center point (0) High level (þ1)
Activation temperature (X1) 400�C 450�C 500�CImpregnation ratio (X2) 2 3 4Activation time (X3) 45 60 75
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on the process conditions as well as on the preliminary experimental runs. Anempirical second-order polynomial model relating the three process variables toresponse variables as represented below was utilized:
Y ¼ b0 þXn
i¼1
biXi
Xn
i¼1
bijXiXj þXn
i¼1
biiX2i ð2Þ
where Y is the predicted response, b0 is a constant, bi is the linear coefficient, bij is theinteraction coefficients, bii is the quadratic coefficients, and Xi and Xj are the codedvalues of the process variables. The results of experiments were analyzed using stat-istical computing software Minitab 15 utilizing the model equation and the analysisof variance (ANOVA).
Results and Discussion
RSM Modeling
The Box-Behnken method was used to construct a polynomial regression equation inorder to analyze the correlation between the process variables and the response vari-ables. The porous carbon yield was found to vary from 37 to 48%, while the MB wasfound to vary from 250 to 470mg=g respectively. The final empirical models in termsof yield (Y1) and MB number (Y2) are given by Equations (3) and (4):
Y1 ¼ 41:37� 1:58X1 � 3:55X2 � 1:08X1X2 þ 0:62X1X3 þ 0:81X21 þ 1:21X2
2 ð3Þ
Y2 ¼ 379:39þ 36:63X1 þ 34:70X2 þ 37:08X3
� 21:21X1X2 þ 34:37X1X3 � 50:05X22 � 25:20X2
3 ð4Þ
Table II. Experimental data
Run X1 (�C) X2 X3 (min) Y1 (% yield) Y2 (MB number)
1 400 2 60 48 3002 500 2 60 46 3263 400 4 60 43 3634 500 4 60 37 3745 400 3 45 44 2956 500 3 45 40 3207 400 3 75 43 3088 500 3 75 41 4709 450 2 45 46 250
10 450 4 45 38 29111 450 2 75 46 31012 450 4 75 40 36513 450 3 60 41 38214 450 3 60 42 38115 450 3 60 41 375
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The appropriateness of a model equation in predicting the experimental responsescan be assessed based on the coefficient of determination (R2). The R2 for yield ofporous carbon was estimated as 0.99, while that of MB was estimated as 0.96, vali-dating the appropriateness of the model. The coefficients of the model equationalong with the significance of each of the model parameters are listed in Tables IIIand Table IV for yield and MB respectively. The lower the value of p or higher thevalue of F or T (F test or T test), the more significant are the model parameters.Table III shows the model parameters X3, interaction parameters X2X3, and thequadratic parameter X2
3 are insignificant for yield, while Table IV shows the interac-tion parameters X2X3 and quadratic parameters X2
1 are insignificant for MB. A teston appropriateness of the model is mandatory as it is used to optimize the process.The validity of the model, in addition to R2, is based on the ANOVA.
Table V shows the results of ANOVA for porous carbon yield. ANOVA is astatistical technique that subdivides the total variation in a set of data into compo-nent parts associated with specific sources of variation for the purpose of testinghypotheses on the parameters of the model (Li et al., 2007). The model F value of101.5 and p>F of 0 indicate the validity of the model. The ANOVA for MB isshown in Table VI. The model F value of 14.7 and p>F value of 0.004 as well implythe appropriateness and validity of the model. From the ANOVA results it can beconcluded that the model predictions using Equations (2) and (3) are satisfactoryand that the model can be utilized to identify the optimum process conditions.
AC Yield
The effects of activation temperature, activation time, and IR on porous carbonyield were studied. Figure 1 shows the 3D surface plot of porous carbon yield withrespect to the activation temperature and IR, while Figure 2 shows the 3D surfaceplot of the effect of activation temperature and activation time on percentage yield,with the other process parameter fixed at the mid-range. The figures indicate that theactivation temperature has a greater effect on the porous carbon yield. The yield wasfound to decrease with increasing activation temperature and IR, while the effect of
Table III. Estimated coefficients using response surfacequadratic model for activated carbon yield
Term Coefficient T P
Constant 41.37 186.7 0.000X1 �1.58 �11.61 0.000X2 �3.55 �26.16 0.000X3 0.10 0.74 0.494
X21
0.81 4.03 0.010
X22
1.21 6.03 0.002
X23
�0.15 �0.73 0.498
X1X2 �1.08 �5.60 0.003X1X3 0.62 3.26 0.023X2X3 0.18 0.91 0.404
R2¼ 99.5%, R2 (adj)¼ 98.5%.
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Table IV. Estimated coefficients using response surfacequadratic model for activated carbon MB number
Term Coefficient T P
Constant 379.39 34.2 0.000X1 36.63 5.38 0.003X2 34.70 5.10 0.004X3 37.08 5.45 0.003
X21
�6.16 �0.61 0.566
X22
�50.05 �4.99 0.004
X23
�25.20 �2.52 0.054
X1X2 �21.21 �2.20 0.079X1X3 34.27 3.56 0.016X2X3 3.34 0.35 0.743
R2¼ 96.4%, R2 (adj)¼ 95.5%.
Table V. Analysis of variance (ANOVA) for the RSM model for activated carbonyield
SourceDegree of
freedom (DF)Sum of
squares (SS)Mean
squares (MS) F P
Model 9 134.60 14.9 101.5 0.000Linear 3 120.75 40.25 273.18 0.000Square 3 7.55 2.52 17.07 0.005Interaction 3 6.31 2.10 14.27 0.007Error 5 0.74 0.15 — —Lack of fit 3 0.73 0.24 73.00 0.014Pure error 2 0.01 0.01 — —Total 14 135.34
Table VI. Analysis of variance (ANOVA) for the RSM model for activated carbonMB number
SourceDegree of
freedom (DF)Sum of
squares (SS)Mean
squares (MS) F P
Model 9 48848.9 5427.7 14.7 0.004Linear 3 31364.6 10454.9 28.21 0.001Square 3 10942.7 3647.6 9.84 0.015Interaction 3 6541.6 2180.5 5.88 0.043Error 5 1852.7 370.5 — —Lack of fit 3 1823.2 607.7 41.15 0.024Pure error 2 29.5 14.8 — —Total 14 50701.7
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activation time was found to be marginal and to have an insignificant effect. Similarresults for the significant impact of activation temperature and insignificant effect ofactivation time (Sudaryanto et al., 2006) have been reported. The highest yield wasobserved at the lowest of activation temperature and IR, in agreement with thereported results (Prahas et al., 2008). The yield in the present work was found tobe in the range of 37 to 48%. Similar results were also reported using phosphoric acidactivation from pecan shells (Guo and Rockstraw, 2007), rubber wood sawdust(Srinivasakannan and Zailani Abu Bakar, 2004), xylan cellulose and kraft lignin(Guo and Rockstraw, 2006), and date stones (Al-Qaessi and Abu-Farah, 2010) inthe open literature. However, a few authors (Lim et al., 2010) have reported a higheryield of 50% at an activation temperature of 425�C and an activation time of 30min,
Figure 1. 3D surface plot of activation temperature and impregnation ratio on % porouscarbon yield (Y1).
Figure 2. 3D surface plot of activation temperature and activation time on % porous carbonyield (Y1).
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possibly due to the lower activation temperature and time. The reduction in yield athigh temperature and IR could be attributed to the reaction of lignocellulose with thephosphoric acid, in which acid first breaks hemicellulose and lignin and hydrolyzesthe glycosidic linkages in the lignocellulose and splits the aryl ether bond in ligninfollowed by dehydration, degradation, and condensation. The aromatic conden-sation reactions also take place as a result of increase in temperature, and evolutionof gaseous products from hydro aromatic structure could also contribute to thereduction in yield (Timur et al., 2006).
MB Uptake
Referring to Table V, activation temperature, IR, and activation time showed signifi-cant effects on the adsorption of MB. Figure 3 shows a 3D response surface plot ofIR and activation temperature on the MB number, whereas Figure 4 shows responsesurface plot of activation time and temperature on the MB number. At low IR andactivation temperature MB uptake was low, while it increased significantly at higherIR and activation temperature. The highest MB adsorption was observed when boththe variables IR and temperature had highest values within the range studied. Inaddition it also indicates an optimum IR, as MB was found to decrease at highIR. An increase in MB indicates an increase in suitability of pore size to accommo-date the MB molecules. As inferred earlier an increase in the activation temperatureas well as the IR contributes towards a decrease in yield, which is a potential measureof the increase in porosity due either to creation of new pores or to enlargement ofexisting pores. Similar observations on the increase in MB uptake with increase inthe activation temperature and IR have been reported (Attia et al., 2008). Addition-ally, Figure 4 shows a significant increase in MB uptake with increase in the acti-vation time at activation temperatures. Similar results of increase in MB uptakewith activation temperature and time have been reported (Chatterjee et al., 2012).Although the statistical analysis indicates activation time to be insignificant due tolow changes in the yield, it brings in a significant change in MB adsorption capacity.A combination of high activation temperature and activation time seems to be
Figure 3. 3D surface plot of activation temperature and impregnation ratio on porous carbonMB uptake (Y2).
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critical in generating the structural changes facilitating large adsorption of MB. Ingeneral the MB adsorption not only depends on physical characteristics of porouscarbon, but also on its chemical nature. At high activation times the change (qualityand quantity) in functional groups may subsequently affect the adsorption capacityof MB. Generally, at high activation times an increase in the aromatic content ofporous carbon functional groups has been recorded (Bacaoui et al., 2001; Wanget al., 2005).
Process Optimization
The optimum process conditions estimated using the optimizer tool in Minitab 15are presented in Table VII, along with the results of repeat runs conducted at theoptimized process conditions. The optimum process conditions were estimated tobe an activation temperature of 400�C, an IR of 3.0, and activation time of 58min,with the resultant porous carbon yield of 44% and MB of 345mg=g. Taking intoconsideration the variations involved in experiments as well as the analysis, theresults are in good agreement with the model prediction, validating the appropriate-ness of the process optimization exercise. It also confirms the suitability of the RSMapproach for optimization of process conditions for preparation of porous carbon.Activation temperatures as low as 400�C have not been reported in the open litera-ture, however, with the exception of Gratuito et al. (2008), who reported the opti-mum temperature of 417�C for phosphoric acid activation of coconut shell. Such
Figure 4. 3D surface plot of activation temperature and activation time on porous carbon MBuptake (Y2).
Table VII. Model validation
X1 X2 X3
% Yield
% Error
MB number%
ErrorPredicted Experimental Predicted Experimental
400 3.0 58.03 44 43 2.3 345 339 1.8
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a low activation temperature coupled with low activation time and high yield renderthese process conditions highly desirable for commercial exploitation.
Structural Characteristics
The structural heterogeneity of porous carbon plays an important role in adsorptionprocesses, and numerous methods have consequently been developed and applied forthe characterization of this property. The present work utilized nitrogen adsorptionisotherm, scanning electron microscopy, and IR methods to characterize the sam-ples. The adsorption desorption isotherms of N2 at �196K for a sample preparedat optimum process conditions along with the sample corresponding to maximumadsorption capacity are shown in Figure 5.
A sharp increase in the amount of nitrogen adsorbed at a relative low pressure of0.1 indicates micropore filling. A typical Type-I isotherm will exhibit a sharp increaseuntil an P=Po of 0.1, beyond which it remains constant, which is characteristic of amicroporous carbon. Figure 5 shows a sharp increase in the amount adsorbed evenbeyond a P=Po of 0.1, with the desorption isotherm showing the presence of hyster-esis loops at relative pressures in excess of 0.4, which are characteristic of a Type-IVisotherm, which additionally substantiates the highly mesoporous nature of thesample. A steep increase in the slope at a high relative pressure (P=Po> 0.8� 1)can be attributed to the development of wider pores and possibly to capillary con-densation in the mesopores (Prahas et al., 2008). It has been reported that porouscarbons prepared at high impregnation ratio and activation temperature possesscharacteristics of the Type-IV isotherm, which indicates the presence of micro- alongwith large amounts of mesopores (Baquero et al., 2003). The BET surface area ofporous carbon was estimated as 725m2=g, while the pore volume and average porediameter were estimated as 1.26 cc=g, and 2.91 nm. The total micropore volume wasfound to be 0.391 cc=g. Although the pore volume is substantially higher, the largepore diameter effectively contributes to the reduction in BET surface area.
The structural heterogeneity of porous material is generally characterized interms of the pore size distribution. The pore size distribution is closely related to
Figure 5. Nitrogen adsorption isotherm of the porous carbon (sample 8: maximum yieldporous carbon sample).
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both kinetic and equilibrium properties of porous material and perhaps is the mostimportant aspect for characterizing the structural heterogeneity of porous materials.The pore size distribution of porous carbon was evaluated by density functionaltheory (DFT), as shown in Figure 6, while the cumulative volume adsorbed withthe pore diameter is shown in Figure 7. Both plots show evidence of the presenceof a larger proportion of mesopores.
The FT-IR absorption spectrum of porous carbon is presented in Figure 8. Itshows a broad band in the 3300–3500 cm�1 region, which could be assigned toOH stretching mode from hydroxyl and phenolic groups involved in hydrogenbonding and may be due to adsorbed water. This is in good agreement with otherresults reported (Bouchelta et al., 2008), and the bands appearing at 1640 and1150 cm�1 are ascribed to the formation of oxygen functional groups, like highlyconjugated C=O stretching in carboxylic groups and carboxylic moieties (Chenet al., 2002).
Figure 6. Differential pore size distributions of porous carbon.
Figure 7. Cumulative pore volume distributions of porous carbon.
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The surface morphology of porous carbon corresponding to the optimized con-ditions is shown in Figure 9. The SEM micrograph confirms presence of large-sizedand nonuniform formation of pores, but clearly indicating presence of a largenumber of pores on the surface.
Figure 8. FT-IR spectra of porous carbon.
Figure 9. SEM image of porous carbon.
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Adsorption Isotherm
Figure 10 shows the equilibrium adsorption isotherms of MB uptake by the porouscarbon at three different temperatures of 30�, 40�, and 50�C. A decrease in the MBuptake with increase in temperature could be attributed to the exothermic nature ofthe adsorption process, as well in concurrence with the general understanding of theadsorption process. The Langmuir and Freundlich isotherm models (Ma et al., 2010)were employed to compare the experimental data with the model to identify anappropriate adsorption isotherm model. Figures 11 and 12 show the Langmuirand Freundlich isotherms respectively in comparison with the experimental dataat 30�, 40�, and 50�C. The suitability of the models can be judged by R2 values,which can be seen in Table VIII along with other parameters. The Langmuirequation is reported to be suitable for homogeneous surfaces, while the Freundlich
Figure 10. Equilibrium adsorption isotherms at 30�, 40�, and 50�C.
Figure 11. Langmuir model fit for adsorption of methylene blue at 30�, 40�, and 50�C.
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equation, suitable for highly heterogeneous surfaces (Wu et al., 2005), often gives agood representation of adsorption data over a restricted range of concentrations.The equilibrium adsorption data in the present work were found to match theFreundlich isotherm better than the Langmuir isotherm, possibly due to the hetero-geneous nature of the porous carbon. The dimensionless factor RL (Vadivelan andKumar, 2005) was found to be 0.131, indicating the favorable nature of the
Figure 12. Freundlich model fit for adsorption of methylene blue at 30�, 40�, and 50�C.
Table VIII. Langmuir and Freundlich isotherm parameters
Temperature�C
Langmuir model parameters Freundlich model parameters
q0 (mg=g) KL R2 Kf (mg=g) (L=g) 1=n R2
30 455 0.0166 0.91 150 0.1528 0.9940 278 0.0083 0.93 57 0.2138 0.9950 238 0.0087 0.94 70 0.1602 0.99
Table IX. Methylene blue number reported by other authors
Source Author Activating agentMB number
(mg=g)
Peach stone Fierro et al., 2010 H3PO4 412Coffee grounds Wang, 2005 H3PO4 181Cotton stalk Bacaoui et al., 2001 H3PO4 245Rice straw Gratuito et al., 2008 H3PO4 110Fibrous rice straw Baquero et al., 2003 H3PO4 107Papaya seeds Bouchelta et al., 2008 H3PO4 97Camellia oleiferashell
Chen et al., 2002 Carbonization at 450�Cfollowed by H3PO4
activation
330
Rice straw Ma et al., 2010 KOH 529
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adsorption isotherm. The maximum mono layer adsorption capacity was estimatedto be 455mg=g, relatively high as compared to the adsorption capacities reported inthe literature for other precursors using phosphoric acid. However, a maximum MBadsorption capacity of 470mg=g corresponds to an activation temperature of 500�C,with the yield lower than the optimized condition. Table IX shows the maximumadsorption capacity of porous carbon for different precursors using H3PO4 activat-ing agent (Attia et al., 2008; Basta et al., 2009, 2011; Collin and Lee, 2008; Denget al., 2011; Fierro et al., 2010; Reffas et al., 2010; Sun et al., 2011).
Conclusions
The following are the key findings of process optimization and characterization ofthe optimized porous carbon prepared from date pits with phosphoric acid:
. Process optimization was performed using response surface methodology (RSM),adopting a Box-Behnken design, for maximizing the yield and MB number. Theoptimized experimental conditions were identified to be an activation temperatureof 400�C, IR of 3, and activation time of 58min, with the resultant porous carbonhaving a yield of 44% and MB adsorption capacity of 345mg=g. Nevertheless,activation temperatures as low as 400�C have not been reported in the openliterature, so low activation temperature coupled with low activation time and highyield render these process conditions highly desirable for commercial exploitation.
. The nitrogen adsorption isotherm indicates a Type-IV isotherm, with the pre-sence of hysteresis loops at relative pressure in excess of 0.4. The structural char-acteristics of the porous carbon reveal the BET surface area to be 725m2=g, with apore volume of 1.26 cc=g, and an average pore diameter of 2.91 nm, with themicropore volume less than 30%.
. The monolayer adsorption of MB using the Langmuir adsorption isotherm wasestimated to be 345mg=g for optimized process conditions, while the maximumMB adsorption capacity of 455mg=g corresponds to the porous carbon with high-est BET surface area. The net positive charge on the surface of porous carbondecreased with increase in pH, resulting in an increase in MB uptake due to thereduction in repulsion between the porous carbon and MB.
. The increase in MB uptake with decrease in temperature indicates that theadsorption process is exothermic. The Freundlich isotherm was found to matchthe experimental data rather than the Langmuir isotherm, owing to the hetero-geneous porous nature of the porous carbon.
Funding
The authors wish to acknowledge the financial support received from The PetroleumInstitute and for giving an opportunity to work on activated carbon research.
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