research article an investigation of biodiesel production from...

Research ArticleAn Investigation of Biodiesel Production from Wastes ofSeafood Restaurants

Nour Sh El-Gendy1 A Hamdy1 and Salem S Abu Amr2

1 Egyptian Petroleum Research Institute PO Box 11727 Nasr City Cairo Egypt2 Environmental Health Directorate Ministry of Health Gaza Strip Palestine

Correspondence should be addressed to Nour Sh El-Gendy nourepriyahoocom

Received 24 May 2014 Revised 18 September 2014 Accepted 18 September 2014 Published 7 October 2014

Academic Editor Abdelwahab Omri

Copyright copy 2014 Nour Sh El-Gendy et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

This work illustrates a comparative study on the applicability of the basic heterogeneous calcium oxide catalyst prepared fromwaste mollusks and crabs shells (MS and CS resp) in the transesterification of waste cooking oil collected from seafood restaurantswith methanol for production of biodiesel Response surface methodology RSM based on D-optimal deign of experiments wasemployed to study the significance and interactive effect of methanol to oil M O molar ratio catalyst concentration reactiontime and mixing rate on biodiesel yield Second-order quadratic model equations were obtained describing the interrelationshipsbetween dependent and independent variables to maximize the response variable (biodiesel yield) and the validity of the predictedmodels were confirmedThe activity of the produced green catalysts was better than that of chemical CaO and immobilized enzymeNovozym 435 Fuel properties of the produced biodiesel were measured and compared with those of Egyptian petro-diesel andinternational biodiesel standards The biodiesel produced using MS-CaO recorded higher quality than that produced using CS-CaO The overall biodiesel characteristics were acceptable encouraging application of CaO prepared from waste MS and CS forproduction of biodiesel as an efficient environmentally friendly sustainable and low cost heterogeneous catalyst

1 Introduction

Development of transesterification process for production ofbiodiesel as an alternative green and sustainable fuel hasbecome an important issue due to diminishing fossil fuelreserves rising crude oil price and the stringent exhaustemission regulations [1]

Biodiesel produced by transesterification reaction can becatalyzed with alkali acid or enzyme in which a primaryalcohol reacts with the triglycerides of fatty acids formglycerol and esters Triglyceride for biodiesel productioncomes from various sources edible and nonedible oil wasteand used oil and fats [2] The major hurdle of applicabilityof biodiesel is the operational cost of its production processapproximately 70ndash95 of the production cost arose fromthe feedstock Homogenous chemical catalyst processesincluding alkali or acid are more practical compared withthe enzymatic method The use of acid catalysts has beenfound to be used for pretreating high free fatty acid feedstock

but the reaction rates for converting triglycerides to methylesters are very slow Enzymes have shown good tolerancefor the free fatty acid level of the feedstock but the enzymesare expensive The use of homogenous basic catalytic processovercome the aforementioned problems but suffers somedrawbacks production of large amount of wastewater fromwashing process of catalyst residues and neutralization stepdifficulty of the product separation and purification andunreusability of the catalysts [3] Heterogeneous catalyticprocess overcomes these drawbacks Among the hetero-geneous solid catalysts calcium oxide CaO has attractedattention due to the elimination of neutralization step highactivity being active inmild reaction conditions long catalystlife time low solubility in methanol lack of toxicity abilityto withstand high temperatures ease of recycling low costand being abundantly available in nature as limestone andits performance for biodiesel production is comparable toseveral homogenous catalysts [4]

Hindawi Publishing CorporationInternational Journal of BiomaterialsVolume 2014 Article ID 609624 17 pageshttpdxdoiorg1011552014609624

2 International Journal of Biomaterials

In Egypt millions of liters of waste cooking oil WCO arediscarded each year into sewage systems Thus it polluteswater streams causing a lot of waste management problemsand consequently adds to the cost of treating effluent Solidwastes density in Egypt averages about 300 kgm3 where60 is organic wastes [5] Thus production of biodieselfrom WCO using CaO prepared from organic wastes (egeggshells mollusks shells crabs shells etc) would offera triple-fact solution economic environmental and wastemanagement

The aim of this work is to optimize biodiesel trans-esterification process using waste cooking oil and calciumoxide catalyst prepared from waste mollusks and crabs shellscollected from seafood restaurants in an attempt to reach aneffective process for practical low cost industrial biodieselproduction

2 Materials and Methods

21 Materials Pure calcium oxide as heterogeneous catalystandmethanol (ARGrade)were purchased fromFlukaChem-ical Corp Gillingham UK Novozym 435 (Candida antarc-tica Lipase B) was a gift from Novozyme AS BagsvaerdDenmark and was supplied as an immobilized enzymeon macroporous acrylic resin Commercial Egyptian petro-diesel was obtained from a local fuelling station

22 Collection and Preparation of Waste Frying Oil andHeterogeneous Catalyst Thewaste frying oilWFOmollusksand crabs shells (MS and CS) were collected from localseafood restaurants and prepared according to El-Gendy etal [3]

The WCO was characterized by high total acidnumber density and viscosity recording 3mgKOHg oil09208 gcm3 and 50 cSt respectively and its saponificationand iodine value were 197mgKOHg oil and 119mgI

2100 g

oil respectively The WCO consists of asymp2436 3635 2868and 1061 palmitic (C160) stearic (C180) oleic (C181)and linoleic (C182) acid respectively

23 Catalyst Characterization The prepared catalysts werecharacterized according to El-Gendy et al [3] using dif-ferential scanning calorimetric-thermal gravimetric analysis(DSC-TGA) and were performed by Q600 SDT Simul-taneous DSC-TGA (New Castle DE USA) a high-reso-lution X-ray diffractometer (XRD PANalytical XrsquoPert PROMPD Netherland) coupled with Cu k120572 radiation source(120582 = 15418 A) Dispersive Raman spectrometer (BRUKER-SENTERRA Germany) equipped with an integral micro-scope (Olympos) energy dispersive X-ray analysis (EDXOxford X-Max England) conjugated with transmission elec-tron microscope TEM (JEM 2100 Jeol Japan) analyticalFourier transforms infrared (FT-IR Perkin Elmer Spec-trum One USA) instrument scanning electron microscope(SEM JEOL-model JSM-53000 Japan) Particle sizer modelBeckman Coulter Multisizer-3 (Nyon Switzerland) was usedfor determination of particle size distribution The specificsurface area of the prepared biocatalysts was measured byBrunauer-Emmett-Teller BETmethod using low temperature

N2adsorption-desorption (NON A3200e Quantachrome

USA) The samples were tested for pore volume and poresize distribution using Barrett-Joyner-Halenda BJH methodTemperature programmed desorption using CO

2as a probe

molecules (CO2-TPD) was used to study basic properties of

the prepared biocatalysts and it was done according toViriya-empikul et al [1]

24 Transesterification The transesterification reactionswere conducted in a laboratory-scale setup according toEl-Gendy et al [3] and the biodiesel yield was calculatedaccording to Boro et al [6] The activity of the preparedbiocatalysts was compared with that of commerciallyavailable most effective heterogeneous basic chemicalcatalyst CaO and immobilized enzyme Novozym 435

25 Experimental Design and Statistical Analysis Based onD-optimal design of experiments twenty runs of experimentshave been conducted for three levels of four independentvariables methanol oil M O (molar ratio 119860) catalyst con-centration (wt 119861) reaction time (min 119862) and mixingrate (rpm 119863) to study their effect on the yield of theproduced biodiesel at constant temperature 60∘C MATLAB70 software (MathWorks USA) was used for experimentaldesign

Once the experiments were preformed the next stepwas to perform a response surface experiment to producea prediction model to determine curvature detect interac-tions among the design factors (independent variables) andoptimize the process that is to determine the local optimumindependent variables with maximum yield of biodiesel Themodel used in this study to estimate the response surfaceis the quadratic polynomial represented by the followingequation

119884 = 120573119900+

119899

sum

119894=1

120573119894119909119894+

119899minus1

sum

119894=1

119899

sum

119895=119894+1

120573119894119895119909119894119909119895+

119899

sum

119894=1

120573119894119894119909

2

119894 (1)

where 119884 is the biodiesel yield (wt) 119899 is the number offactors 120573

119900is the intercept term 120573

119894 120573119894119895 and 120573

119894119894are the linear

interactive and quadratic coefficients respectively 119909119894rsquos are

the levels of the independent variables (factors) under studyThe statistical software Design Expert 607 (Stat-Ease

Inc Minneapolis USA) was used for regression and graphi-cal analyses of the data obtained and statistical analysis of themodel to evaluate the analysis of variance (ANOVA)

26 PhysicochemicalCharacterization of the ProducedBiodieselTheproduced biodiesel was tested for estimating and evaluat-ing its fuel properties using the standardmethods of analysisfor petroleum products American Society for Testing andMaterials ASTM standards methods [7] The results werecompared with the Egyptian standards for petro-diesel andEuropean andAmerican standards of biodiesel (EN14214 andD-6751 resp) [8 9]

All the properties were analyzed in two replicates and thefinal results given below were obtained as the average values

International Journal of Biomaterials 3

0

20

40

60

80

100

0 200 400 600 800 1000

Hea

t flow

(Wg

)

Wei

ght l

oss (

)

Weight loss ()Heat flow (Wg)


Mollusks shells

minus6

minus5

minus4

minus3

minus2

minus1

0

Temperature (∘C)

Hea

t flow

(Wg

)

Wei

ght l

oss (

)

Temperature (∘C)

0

20

40

60

80

100

0 200 400 600 800 1000

Crabs shells

minus5

minus45

minus4

minus35

minus3

minus25

minus2

minus15

minus1

minus05

0

Figure 1 TGADSC curves

3 Results and Discussion

31 Catalyst Characterization The thermal transition duringthe calcination process of each collected waste shells wasinvestigatedwithTGADSC Figure 1 shows the thermal anal-ysis results along with the weight loss when the temperaturewas raised from room temperature to 1100∘C

The thermogravimetric analysis of MS shows that therewas no significant decomposition occurred upon heatingup to 600∘C recording weight loss of asymp5 The dominantdecomposition asymp41 weight loss occurred within 700ndash800∘C(peaked at 778) and remained sustained thereafter up to1100∘C The DSC curve supports the TGA curve where theheat flow chart illustrates endothermic peak at 778∘C Thisreveals the production of new compound

Upon calcination of CS the TGA analysis reveals threephases of mass loss with a total weight loss of asymp5677 Thefirst mass loss was observed at temperatures below 200∘Crecording weight loss of asymp5 (peaked at 170∘C) The secondmass loss occurred within 250ndash400∘C recording weight lossof asymp20 (peaked at 320∘C) The dominant decompositionwithasymp30weight loss occurredwithin 650ndash770∘C (peaked at750∘C) and remained sustained thereafter up to 1100∘C TheDSC curve shows an exothermic peak at 130∘C Accordingto Boro et al [6] this can be attributed to evaporationof water crystallization decomposition of organic compo-nents or possible rearrangement in the structural arrange-ment within the compound itself The DSC curve showsalso a weak broad endothermic peak located at the range320ndash370∘C and another sharp endothermic peak at 753∘CThe two endothermic peaks might indicate the decomposi-tion of compounds and formation of a new one

According to N B Singh and N P Singh [10] the weightloss might be attributed to the decomposition of CaCO

3

through the loss of carbon dioxide CO2and production of

calcium oxide CaO and also due to the possible removalof absorbed water molecules which occurs according to thefollowing dissociation equation

CaCO3(s) 997888rarr CaO (s) + CO

2(g) (2)

It was observed that during calcination the MS andCS turned completely pale grey and white respectivelyAccording to Engin et al [11] this indicates that calcium car-bonate CaCO

3is converted to CaOwith elevating calcination

temperaturesThe XRD patterns of natural MS (Figure 2) are mainly

aragonite CaCO3(JCPDS card number 024-0025) and upon

calcination at 400∘C it was changed to calcite CaCO3(JCPDS

card number 005-0586) and remained unchanged up tocalcination at 600∘C while calcination at 700∘C showedmixture of calcite CaCO

3(JCPDS card number 005-0586)

and lime CaO (JCPDS card number 043-1001) The XRDpatterns showed a pure crystallineCaO (JCPDS card number043-1001) for calcination temperatures 800ndash1100∘C whilethe XRD patterns of CS revealed that the natural CS iscomposed mainly of crystalline calcite CaCO

3(JCPDS card

number 005-0586) and also to a minor extent of mono-hydrocalcite CaCO

3sdotH2O (JCPDS card number 022-0147)

Upon calcination at 400∘C CaCO3sdotH2O was lost and only

calcite CaCO3(JCPDS card number 005-0586) detected

and remained unchanged up to calcination at 600∘C TheXRD patterns showed a pure crystalline calcia or burntlime CaO (JCPDS card number 004-0777) for calcinationtemperatures 700ndash1100∘C The obtained XRD patterns couldexplain the TGADSC flowcharts of CS where the weakbroad endothermic peak at the range of 320ndash370∘C might bedue to the loss of water and decomposition of CaCO

3sdotH2O

and the sharp one at 753∘Cmight be due to the decompositionof CaCO

3and formation of CaO

Narrow and high intense peaks of the calcinated MS andCS (at temperature ge800 and 700∘C resp) could define thewell-crystallized nature of the prepared biocatalyst similarobservation which was reported by Boey et al [2] and Viriya-empikul et al [12] on preparation of biocatalyst from wastemud crab shells (Scylla serrata) and waste mollusk shells forbiodiesel production from palm olein oil

The crystal size was calculated from the XRD data(Table 1) recording asymp4215 nm for natural MS whichdecreased upon calcination at 800∘C recording asymp3877 nmSimilar observation was reported by Yoosuk et al [13] who


10 20 30 40 50 60

Cou

nts

0

500

Chemical CaO

Position (∘2120579) (copper (Cu))

10 20 30 40 50 60

Cou

nts

0200400

0100200

050

050

0400600

0200400

0200400

0200400

0100

1100

1000

900

800

700

600

500

400

Natural

MS

Position (∘2120579) (copper (Cu))10 20 30 40 50 60

Cou

nts

0200

0200400

0200

0200400

0200400

0200300

0100200

0100200

050

100

1100

1000

900

800

700

600

500

400

Crabs shells

CS


Figure 2 XRD patterns during calcination at different temperatures

attributed this to the presence of water molecules duringcalcination of CaCO

3to CaO But the crystalline size of

the uncalcinated CS was found to be asymp3215 nm and itwas slightly increased by calcination at 700∘C recordingasymp3282 nm Borgwardt [14] and Liu et al [15] reported thatcalcination of CaCO

3leads to formation and growth of CaO

When CaCO3decomposes at high temperatures small CaO

grains formed and then the contact grains form necks andbegin to grow resulting in an increase in the average grainsize

Raman spectra (Figure 3) are consistent with the XRDpatterns In case of natural MS the vibration bands at 155197 650 703 and 1086 cmminus1 correspond to those of aragoniteCaCO

3The vibration bands at 360 1075 1334 and 1463 cmminus1

of calcined MS at 800∘C correspond to pure lime CaO whilethe vibration bands at 155 282 714 and 1087 cmminus1 of naturalCS correspond to calcite CaCO

3 The high vibration bands at

360 960 and 1075 cmminus1 of calcined CS at 700∘C correspondto pure burnt lime CaO

EDX analysis confirmed also the results obtained fromXRD and Raman The EDX analysis (Table 2) revealed thatthe chemical composition of the shells was highly affectedby calcination The uncalcinated shells exhibit oxygen asthe main component 5662 and 5369 wt while incalcinated shells at 800∘C and 700∘C calcium representsthe major component (6232 and 4989 wt) for MS andCS respectively Similar observation was reported by Viriya-empikul et al [12] and Birla et al [16] where the maincomponent in the calcinated shells was calcium and otherelements for example Na Mg and so forth were found intrace amounts Stoichiometrically this is true as in CaO Cais themain constituent (asymp71) while oxygen is themajor onein CaCO

3(asymp48)

The basicity of the prepared CaO from MS and CSrecorded 5218 and 27mmol CO

2g respectively This might

affect the activity of the catalyst in the transesterificationreaction where the mechanism of CaO in transesterificationreactionswould be started by dissociation of CaO (Scheme 1)Then oxide anion attacks the methanol to form methoxideanion which is why excess methanol is required to drivethe reaction in the forward direction The methoxide anionattacks the carbonyl carbon of the triglyceride to form atetrahedral intermediate The rearrangement of the interme-diate molecule forms a mole of methyl ester and diglycerideAnother methoxide anion attacks the carbonyl carbon in theformed diglyceride forming another mole of methyl esterand monoglyceride Finally a new methoxide anion attacksthemonoglyceride producing a total of threemoles ofmethylesters and a mole of glycerol

The FTIR patterns of MS and CS with respect to calcina-tion process (Figure 4) were nearly the same showing majorpeaks around 1420ndash1471 860ndash874 and 709 cmminus1 in patternsof natural shells which disappeared in that of calcinatedshells According to Engin et al [11] these peaks are attributedto asymmetric stretch out-of-plane bend and in-plane bendvibration modes for CO

3

minus2 moleculesThe strong sharp peakat 3643 cmminus1 in uncalcinated CS confirms the XRD patternand presence of CaCO

3sdotH2O Also upon calcination weak

bands around 2509 and 1786ndash1793 cmminus1 disappeared and newweak peak appeared at 1111 cmminus1 for calcinated MS and 1089and 1056 cmminus1 for calcinated CS The observed changes inIR patterns might indicate the complete transformation ofCaCO

3to CaO Similar observation was reported by Roschat

et al [17]In the viewpoint of preparation time energy consumption

and cost of catalyst preparation the temperatures of 800∘C


CS1600

1400

1200

1000

800

600

400

200

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural crabs

700∘C

Wavenumber (cmminus1)

shells

MS150

100

50

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural mollusks

800∘C


shells

Figure 3 Raman spectra at different calcination temperatures

40000 3000 2000 1500 1000 4000100

20304050607080

900

Natural mollusks shells

3414

2522

16381617

1471

860621

477

3549

3225

3476

29152848

1786 1082709

6982022

(cmminus1)

T(

)

800∘C

(a)

40000 3000 2000 1500 1000 4000100

20304050607080

900

Natural crabs shells3550

3414

3236

2030

1637 1420

1083874

619

3468

25091793

2856

3642 1617

1469

1056

4802915 709

1089

(cmminus1)

T(

)700

∘C

(b)

Figure 4 FTIR spectra of mollusks shells (a) and crabs shells (b) at different calcination temperatures

OCOR1

OCOR2O

OndashCndashR3

CH3Ominus

OCOR1

OCOR2Ominus

OndashCndashR3

OCH3

OCOR1

OCOR2

Ominus

R3ndashCndashCH3

O

+

O2minus+ CH3OH harr OHminus

+ CH3Ominus

OHminus+ CH3OH harr H2O + CH3Ominus

CaO harr Ca2++ O2minus

Scheme 1

and 700∘Cwere selected as perfect calcination temperature toprepare biocatalysts from natural waste mollusks and crabsshells respectively

The morphology of natural and calcined shells wasinvestigated by SEM at equal magnification of 500x SEMmicrograph of catalyst derived from MS (Figure 5(b)) showsthat upon calcination the morphology of MS changed fromlayered bulky substances without any clear pores on itssurface (Figure 5(a)) to porous particles of various sizes and

shapes with higher specific surface area The SEM micro-graphs of the natural crabs shells (Figure 5(c)) showed bulkyand nonuniform clustered substances with clear pores on itssurface which transformed to relatively similar aggregatesof porous smaller particles with higher specific surface areaupon calcination at 700∘C (Figure 5(d)) This porosity isprobably due to the fact that a large number of gaseouswater molecules are released upon the decomposition ofCaCO

3sdotH2O Hu et al [18] reported that the gaseous water

molecules create high porosity in the catalyst that is to act asporogens

The particles size distribution (Table 1) proved the SEManalysis (Figure 5) where a large part of the particles sizedistribution of the natural MS and CS was within thesize range of 858ndash1723 and 901ndash1843 120583m while the restwas within the range of 648ndash713 and 652ndash725 120583m withoverall average particles diameter of asymp1107 and 1027 120583mrespectively But upon calcination at 800 and 700∘C theparticles size decreased where a large part of the particlessize distribution was in the range of 793ndash1450 and 771ndash1074 120583m and the rest was within the range of 637ndash680and 638ndash681 120583m with overall average particles diameter ofasymp986 and 824 120583m respectivelyThe smaller size of the grainsand aggregates would provide higher specific surface areas


Table 1 Some characteristics of the prepared biocatalysts

Parameters Natural MS MS at 800∘C Natural CS CS at 700∘CCrystal size nm 4215 3877 3215 3282Average particle size 120583m 1107 986 1027 824119878BET m

2g mdash 1263 mdash 4373Pore volume cm3g mdash 0046 mdash 0211Pore size nm mdash 094 mdash 184Basicity mmol CO2g mdash 5218 mdash 27

Table 2 Chemical composition of biomass derived catalysts

Biomass Chemical composition (wt)Natural mollusks shells C (1735) Mg (001) Ca (2601) O (5662)Calcinated mollusks shells at 800∘C C (347) Mg (005) Ca (6232) O (3416)Natural crabs shells C (1444) Na (11) Mg (092) Ca (2985) O (5369)Calcinated crabs shells at 700∘C C (792) Na (003) Mg (053) Ca (4989) O (4163)

Because the prepared biocatalyst has relatively large particlesizes it is easy to separate the catalyst from the products afterthe reaction by filtration or centrifugation

The BET surface area SBET of the prepared catalysts(Table 1) recorded 1263 and 4373m2g for CaO preparedfrom MS and CS respectively This coincides with the SEMobservation (Figures 5(b) and 5(d)) The BJH method wasused for calculations of the pore size distributions (Table 1)and the prepared biocatalyst recorded total pore volumeof asymp0046 and 0211 cm3g respectively and the pore sizedistributed between asymp083 and 1718 nm and between 104and 1558 nm with average pore diameter of 094 and184 nm respectively indicating that most of the pore sizedistributions are found in the microporous range Accordingto Roschat et al [17] a high porosity catalyst is a keyrequirement to achieve high conversion efficiency for hetero-geneous process thereby high surface area or high catalyticsites are necessary Sharma et al [19] also reported a highpore size to be desirable for better diffusion of reactantsand product molecules Thus this would recommend thebiocatalyst prepared from MS and CS for application inbiodiesel production

The N2adsorption-desorption isotherms of the prepared

CaO fromMS and CS are shown in Figures 6(a) and 6(b) andthey are of type II isotherm (based on IUPACrsquos classification)with a low slope in the middle region of the isotherm and adesorption curve almost overlapping with adsorption curveApplying BET equation 119875119875

119900= 09590 and 09482 (lt1) and

119862 = 7152 and 17012 (gt1) respectively indicating monolayerformation The positive curvature at the lowest pressuresindicates a distribution of adsorption energiesThe isothermshave a hysteresis loop of H3 and slopping adsorption anddesorption branches covering a large range of 119875119875

119900with

underlying type II isotherm

32 RegressionModel and Its Validation Thecomplete designmatrix with experimental and predicted values of yieldof biodiesel using different CaO catalyst prepared frommollusks and crabs shells is presented in Table 3 Based

on D-optimal design and experimental data two second-order quadratic models for the applied catalysts have beenpredicted and can be given as follows

1198841= 8243 minus 221119860 minus 098119861 + 312119862 + 080119863 + 448119860

2

+ 189119861

2minus 751119862

2minus 256119863

2minus 266119860119861 minus 116119860119862

+ 579119860119863 + 250119861119862 + 842119861119863 + 087119862119863

(3)

1198842= 8505 + 341119860 minus 328119861 minus 505119862 minus 06119863

minus 219119860

2+ 463119861

2+ 190119862

2+ 004119863

2+ 489119860119861

minus 056119860119862 + 032119860119863 minus 3194119861119862 minus 545119861119863 + 253119862119863

(4)

where 1198841and 119884

2are the biodiesel yields from transesterifica-

tion processes using biocatalyst prepared from MS and CSrespectively

Positive sign in front of the terms indicate synergeticeffect whereas negative sign indicates antagonistic effect

Pareto charts which are very useful in design of exper-iments were used in this work to make it much easier tovisualize the main and interaction effects of all factors to theresponse variable that is biodiesel yield (Figure 7)

In case of using biocatalyst prepared from MS in thetransesterification process reaction time has a high positiveimpact on the reaction yield followed by the mixing rateBut M Omolar ratio has a high negative impact followed bycatalyst loading The interaction effects of M O molar ratioand catalyst loading have a higher negative impact thanM Oand reaction time on the biodiesel yield while the interactiveeffect of catalyst loading and mixing rate expresses a veryhigh positive impact on the biodiesel yield coming after itthe interaction between M O ratio and mixing rate catalystloading and reaction time in a decreasing order and theinteractive effect of reaction time and mixing rate has a lowpositive impact on the reaction yield

In case of using biocatalyst prepared from CS in thetransesterification process only the M O molar ratio has


(a) (b)

(c)

(d)

Figure 5 SEM images of natural mollusks shells (a) calcined mollusks shells at 800∘C (b) natural crabs shells (c) and calcined crabs shellsat 700∘C (d)

positive impact that is increasing the M O would increasethe biodiesel yield But reaction time has a high negativeimpact followed by catalyst concentration and mixing ratein a decreasing order that is their increase would lowerthe biodiesel yield The positive interactive impact on thebiodiesel yield was expressed by M O and catalyst loadingreaction time andmixing rate andM O andmixing ratewitha decreasing order While the interaction between catalystloading and mixing rate catalyst loading and reaction timeand M O and reaction time has negative impact on thebiodiesel yield in a decreasing order

The validity of the fitted models (3) and (4) was evaluatedand their statistical significance was controlled by 119865-testThe analyses of variance (ANOVA) for the response surfacefull quadratic models are given in Tables 4 and 5 It can beindicated that the models are highly statistically significantat 95 confidence level with 119865 value of 94012 and 9958with very low probability 119875 value of lt00001 respectivelythat is there is less than 001 chance that this error iscaused by noiseThe values of the determination coefficients119877

2 and 1198772adj which measure the model fitting reliabilityfor the models (3) and (4) were calculated to be (09996


0 02 04 06 08 1

DesorptionAdsorption

minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)

Figure 6 N2adsorption-desorption isotherm of calcined MS at 800∘C (a) and CS at 700∘C

A B C D A2 B2 C2 D2

Mollusks shells CaO10

8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)

Figure 7 Pareto chart showing the effects of different independent variables on biodiesel yield

09986) and (09964 and 09864) respectively This suggeststhat approximately 9996 and 9964 of the variance isattributed to the variables and indicated a high significance ofthe predictedmodelsThus only 004 and 036 of the totalvariations cannot be explained by the models respectivelywhich ensures the good adjustment of the above models tothe experimental data Confirmation of the adequacy of theregression models was reflected also by the good agreementbetween experimental and predicted values of responsevariables as shown in Table 3 where the actual biodiesel yieldfor mollusks and crabs shells biocatalyst ranged from 7180 to92 and from 74 to 97 and there corresponding predictedvalues are 7180 and 9175 and 74 and 9650 respectivelyldquoAdeq Precisionrdquo measures the signal-to-noise ratio A ratiogreater than 4 is desirable The ratio of 10201 and 36452respectively indicated an adequate signal These models arereliable and can be used to navigate the design space

The relationship between predicted and experimentalvalues of biodiesel yield for CaO prepared from MS andCS is shown in Figures 8(a) and 8(b) It can be seen thatthere is a high correlation (1198772 asymp 1) between the predictedand experimental values indicating that the predicted andexperimental values were in high reasonable agreement It

means that the data fit well with the model and give aconvincingly good estimate of response for the system in theexperimental range studied

The perturbation plots in Figures 9(a) and 9(b) showthe comparative effects of all independent variables on thebiodiesel yield The curvatures of the four factors fromthe center point confirm the statistical data obtained fromanalysis of variance (ANOVA Tables 4 and 5) that is thesignificance of each parameter (coefficient) In case of CaOprepared from MS (Figure 9(a)) the sharp curvature ofthe two factors M O (119860) and reaction time (119862) showsthat the response biodiesel yield was very sensitive to thesetwo variables The comparatively low curvature of catalystconcentration (119861) and mixing rate (119863) curves shows lesssensitivity of biodiesel yield towards the change in thesetwo factors The curvatures also confirm the data illustratedin Pareto chart (Figure 7(a)) where the increase of M Omolar ratio decreases the biodiesel yield while the increase inreaction time increases the biodiesel yield The sensitivity ofbiodiesel yield towards the four variables can be ranked in thefollowing decreasing order reaction time gt MO gt catalystconcentration gt mixing rate In case of CaO prepared fromCS (Figure 9(b)) all the parameters within the studied range


Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)

Figure 8 Actual versus predicted biodiesel yield using mollusks (a) and crabs (b) shells-CaO

Deviation from reference point

Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)

Figure 9 Perturbation plot for biodiesel yield in case of mollusks (a) and crabs (b) shells-CaO

have highly significant effect on the biodiesel yield exceptthe mixing rate (119863) which has relatively nonsignificant effectThe curvatures also confirm the data illustrated in Paretochart (Figure 7(b)) where the increase of M O molar ratioincreases the biodiesel yield while the increase of reactiontime catalyst loading and mixing rate decrease the yieldwith decrease of sensitivity (reaction time gtMO asymp catalystconcentration ≫ mixing rate) These observations are wellmatched to the model mathematical equations (3) and (4)

33 ResponseSurfaceMethodology Three-dimensional responsesurface graphical diagrams of the regression equations (3)and (4) were plotted (Figures 10 and 11) to understandthe interactive relationship between the independent vari-ables and yield of biodiesel and determine the optimumconditions for maximum biodiesel production using CaOprepared fromMS and CS respectively

Figure 10(a) illustrates the effect of M O molar ratio andthe preparedMS-CaO concentration on biodiesel production


Table 4 Analysis of variance of the fitted quadratic regression model (3)

Source SSlowast dflowast MSlowast 119865 value 119875 value RemarksModel 67125 14 4795 94012 lt00001 Highly significant119860 4697 1 4697 92097 lt00001 Highly significant119861 306 1 306 5998 00006 Highly significant119862 1850 1 1850 36276 lt00001 Highly significant119863 214 1 214 4194 00013 Significant119860

2 1646 1 1646 32279 lt00001 Highly significant119861

2 263 1 263 5152 00008 Highly significant119862


2 507 1 507 9936 00002 Highly significant119860119861 680 1 680 13327 lt00001 Highly significant119860119862 184 1 184 3617 00018 Significant119860119863 3302 1 3302 64750 lt00001 Highly significant119861119862 884 1 884 17338 lt00001 Highly significant119861119863 2839 1 2839 55671 lt00001 Highly significant119862119863 108 1 108 2119 00058 SignificantResidual 026 5 0051Corrected total 67150 19lowastSS sum of squares df degree of freedom MS mean square


Source SSlowast dflowast MSlowast 119865 value 119875 value RemarksModel 70818 14 5058 9958 lt00001 Highly significant119860 11175 1 11175 21998 lt00001 Highly significant119861 3440 1 3440 6772 00004 Highly significant119862 4863 1 4863 9573 00002 Highly significant119863 120 1 120 237 01845 Nonsignificant119860

2 392 1 392 773 00389 Possibly significant119861

2 1577 1 1577 3105 00026 Significant119862


29279119864 minus 004 1 9279119864 minus 004 1827119864 minus 003 09676 Nonsignificant

119860119861 2296 1 2296 4520 00011 Significant119860119862 043 1 043 084 04021 Nonsignificant119860119863 010 1 010 020 06720 Nonsignificant119861119862 1440 1 1440 2835 00031 Significant119861119863 1188 1 1188 2339 00047 Significant119862119863 921 1 921 1813 00080 SignificantResidual 254 5 051Corrected total 71072 19lowastSS sum of squares df degree of freedom MS mean square

at a constant reaction time of 30min and mixing rate of200 rpm The increase of M O ratio and catalyst loadingdecreased the biodiesel yield The maximum yield asymp92occurred within the range 6 1ndash65 1 M O and 3ndash45 wtcatalyst concentration but further increase in M O andcatalyst slightly decreased the biodiesel yield to asymp84 at 6 1and 9wt 89 at 12 1 and 6wt and 81 at 12 1 and 9wtM O higher than the stoichiometric ratio has generally beenadopted for biodiesel production But further increase inM Owould lower the biodiesel yield as itmight have dilutioneffect on the catalyst concentration Glycerol would dissolve

in excessive methanol and subsequently inhibit the reactionof methanol with oil and catalyst Also the separation ofglycerol would be difficult which would consequently shiftthe equilibrium in the reverse direction [20]

Figure 10(b) represents the effect of M O molar ratioand reaction time on biodiesel production at a constantcatalyst concentration 3wt and mixing rate 200 rpm Itseems within the studied range of experiments the increaseof reaction time increased the biodiesel yield recordingasymp92 at 6 1ndash65 1 M O and 75ndash93min molar ratio Thehigh basicity of MS-CaO enabled transesterification in short


reaction time But the biodiesel yield slightly decreased withfurther increment of M O molar ratio and time reachingasymp86 at 12 1 M O and 120min The decrease in biodieselproduction at higher reaction time might be due to thesaturation of the active sites of the catalyst

Figure 10(c) represents the effect of M O andmixing rateon biodiesel production at a constant reaction time 30minand MS-CaO concentration 3wt Biodiesel productionrecorded its maximum yield asymp92 at 6 1ndash65 1 M O and200ndash250 rpm further increment to 12 1 M O and 400 rpmdecreased the yield to asymp86

Figure 10(d) shows the interactive effect of mixing rateand CaO concentration It is obvious from the 3D plot thehigh positive interaction of these factors at low catalystloading and high rpm the biodiesel yield increased recordingasymp81 at 3wt and 400 rpm and also at high catalyst loading9wt and low mixing rate 200 rpm But at low mixing rate200ndash250 rpm and catalyst loading 3wt the biodiesel yieldwas high asymp92

Figure 10(e) shows the interactive effect of mixing rateand reaction time at a constant 6 1 M O and MS-CaOconcentration 3wt It is obvious that increasing the mixingrate and reaction time increased the yield to a certain extentrecording asymp92 at 200ndash250 rpm and 75ndash93min Furtherincrement of mixing rate decreased the yield recording asymp81at 400 rpm and 30min and 84 at 400 rpm and 120min

Figure 10(f) presents the interaction between reactiontime and catalyst concentrationThe increases of both factorsdecrease the biodiesel yield recording maximum yield asymp92at 3ndash45 wt and 75ndash93min

From the RSM analysis it can be concluded that themaximumbiodiesel production 89minus92 using CaO preparedfrom mollusks shells MS-CaO can be achieved over a widerange of experimental parameters at 6 1ndash65 M O molarratio 3ndash45 wt catalyst concentration 75ndash93min reactiontime and mixing rate of 200ndash250 rpm at 60∘C

Figure 11(a) illustrates the effect of M O molar ratioand CS-CaO catalyst loading on biodiesel production at aconstant reaction time of 120min and mixing rate 400 rpmAt low M O ratio the increase of catalyst concentrationdecreased the biodiesel yield recording asymp796 yield at 6 1M O and 9wt catalyst concentrationThis can be explainedby the effect of mass transfer limitation with the presenceof excess solid catalyst But at high M O ratio the biodieselyield increased with increase of catalyst loading recordingmaximum biodiesel yield of approximately 97 at asymp105 1ndash12 1 M O and 75ndash9 catalyst loading (ww) According toSon et al [20] a molar ratio of methanol to oil M O higherthan the stoichiometric ratio has generally been adoptedfor biodiesel production as methanol would promote theformation of methoxy anions on the catalyst surface leadingto a shift in the equilibrium in the forward direction thusincreasing the biodiesel yield

Figure 11(b) represents the effect of M Omolar ratio andreaction time on biodiesel production at a constant catalystconcentration 3wt and mixing rate 400 rpm It seems thatat low and highM O the increase in reaction time decreasesthe yield recording asymp80 at 6 1M O and 120min and asymp93at 12 1 M O and 120min but asymp97 at 12 1 M O and 30min

Figure 11(c) represents the effect of M O and mixing rateon biodiesel production at a constant reaction time 120minand catalyst loading 3 The 3D plot shows that at low andhigh M O the increase in mixing rate decreases the yieldrecordingasymp97 at 12 1M O and 200 rpmbutasymp93 and 80at 400 rpm using 12 1 and 6 1 M O respectively

Figure 11(d) shows that there is a negative interactiveeffect between these two factors where at low mixing rateincreasing the catalyst concentration increased the biodieselyield recording 80 and 97 at 200 rpm using 3 and 9wtcatalyst respectively But at high mixing rate 400 rpm theopposite occurred increasing the catalyst loading decreasedthe yield recordingasymp93 and 97 at 9 and 3wt catalyst load-ing respectively The separation phase between hydrophilicmethanol and hydrophobic oil and between the two liquidreactants and solid catalyst is generally known to be majorproblem lowering the biodiesel yield in heterogeneous pro-cess Thus increasing the stirring rate would increase themixing of the reactants which would consequently promotethe transesterification process as the mass transfer of thereactants to the catalyst surface can be enhanced Furtherincrease in the stirring velocity would lead to increase inturbulence in the reaction mixture which would lower thebiodiesel yield Also the increase of catalyst concentrationwould increase the active sites of the solid catalyst availablefor the transesterification process

Figure 11(e) shows the interactive effect of mixing rateand reaction time It is obvious that increasing the mixingrate to a certain limit 200ndash300 rpm with increase of reactiontime 30ndash50min yields larger amount of biodiesel recordingits maximum asymp97 Further increase of mixing rate slightlydecreased the biodiesel yield recording asymp93 at 400 rpm and120min and asymp89 at 400 rpm and 30min

Figure 11(f) presents the negative interaction betweenreaction time and catalyst loading The increase of catalystloading and reaction time decreased the biodiesel yield toreach asymp80 at 9wt catalyst concentration and 120minThe maximum biodiesel yield asymp97 occurred at 9 catalystconcentrations and 30min reaction time and asymp93 at 3catalyst concentrations and 120min reaction time Accordingto Zhang et al [21] the reason for the reduction in biodieselyield with excess catalyst may be attributed to increase inviscosity of reaction mixture which might result in masstransfer limitation

From the RSM analysis it can be concluded that themaximum biodiesel production using CaO prepared fromcrabs shells CS-CaO can be achieved at 105 1ndash12 1 M O75ndash9 catalyst concentration 30ndash50min reaction time andmixing rate of 200ndash300 rpm at 60∘C

34 Optimization of the Transesterification Process The opti-mization process was carried out to determine the optimumvalue of biodiesel production efficiency using the DesignExpert 607 software According to the software optimizationstep the desired goal for each operational condition (119860MO 119861 catalyst concentration 119862 reaction time and 119863mixing rate) was chosen ldquowithinrdquo the studied range Theresponses ( biodiesel yield) were defined as maximum to


813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90

Catalyst concentrationM

O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000

Catalyst concentration

Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)

Figure 10 Response surface plots of biodiesel yield using CaO prepared from waste mollusks shells


795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)

Figure 11 Response surface plots of biodiesel yield using CaO prepared from waste crabs shells

achieve the highest performance The program combinesthe individual desirability into a single number and thensearches to optimize this function based on the response goalAccordingly the optimum working conditions and respec-tive biodiesel production were established The maximum

predicted biodiesel yields 94 and 100 were found to beachieved at 6 1 and 12 1 M O 45 and 73 catalyst wt82 and 30min reaction time and 220 and 214 rpm mixingrate in case of using biocatalyst prepared from mollusksand crabs shells respectively The desirability function value


Table 6 Physicochemical properties of the produced biodiesel using CaO prepared from waste MS and CS compared to internationalstandards of biodiesel and Egyptian petro-diesel standard specifications

Test UnitProduced biodiesel Egyptian

perto-dieselstandards

BiodieselEN14214

BiodieselD-6751Mollusks shells

CaOCrabs shells

CaODensity at 1556∘C gcm3 08914 09003 082ndash087 086ndash09 mdashSpecific gravity 08924 09011 mdash mdash mdashAPI 2706 2553 mdash mdash mdashKinematic viscosity at 40∘C cSt 55 76 16ndash7 35ndash5 19ndash6Pour point ∘C minus2 minus2 45 mdash mdashCloud point ∘C 1 1 mdash mdash mdashTotal acid number mgKOHg 06 07 Nil lt05 lt08Total S wt 0003 0006 lt12 lt001 lt005Water content ppm 312 300 1500 lt500 lt500Flash point ∘C 148 143 gt55 gt101 gt130Calorific value MJKg 3815 3555 gt443 329 mdashIodine number mg I2100 g 105 108 mdash lt120 mdash

was found to be 1000 for these optimum conditions Anadditional experiment was then performed to confirm theoptimum results The laboratory experiment agrees well withthe predicted response values asymp96 and 98 respectivelyThat indicates the process optimization based on D-optimaldesign of experiments was capable and reliable to optimizebiodiesel production fromwaste cooking oil using biocatalystprepared from MS and CS The lower required amounts ofmethanol and catalyst concentrations in case of transesterifi-cation using MS-CaO relative to those using CS-CaO mightbe attributed to the recorded higher basicity of MS-CaOrelative to that of CS-CaO

Boey et al [2] reported the optimum conditions forproduction of biodiesel (asymp98) from palm olein oil usingCaO prepared from waste mud crab shells by calcinationabove 700∘C for 2 h to be 05 1 M O g g 5 wt catalystconcentration 25 h 500 rpm and 65∘C

Correia et al [22] reported the production of 831biodiesel yield from sunflower oil using CaO prepared fromwaste crabs shells calcinated at 900∘C for 2 h using thefollowing conditions 6 1 M O molar ratio 3 wt catalystconcentration 4 h 1000 rpm and 60∘C

Viriya-empikul et al [1] reported 92 biodiesel yieldfrom palm olein oil using CaO prepared fromwaste mollusksshells by calcination at 800∘C for 2 h to be 18 1 M O molarratio 10 wt catalyst concentration 2 h and 60∘C

35 Comparing the Efficiency of the Prepared Catalyst withChemical CaO and Novozym 435 The activity of the pre-pared MS-CaO and CS-CaO using the obtained optimumconditions for production of biodiesel was compared withthat of commercially available most effective heterogeneousbasic catalysts CaO and Novozym 435

At optimum conditions of MS-CaO 6 1 M O 45 cat-alyst wt 82min 220 rpm and 60∘C the achieved biodieselyield was asymp95 83 and 40 using MS-CaO chemical CaOand Novozym 435 respectively While applying the optimum

operating conditions for CS-CaO 12 1M O 73 catalyst wt30min 214 rpm and 60∘C the biodiesel yield recorded asymp9778 and 35 using CS-CaO chemical CaO and Novozym435 respectively That indicates the higher efficiency of theproduced MS-CaO and CS-CaO for production of biodieselin comparison with the commercial chemical CaO and themost widely used enzyme Novozym 435

36 Physicochemical Characterization of the Produced BiodieselUsing CaO Prepared from MS and CS The produced bio-diesel using the obtained optimum transesterification condi-tions of each of the prepared biocatalysts was evaluated on thebasis of its fuel properties compared to Egyptian petro-dieseland international biodiesel standards as shown in Table 6All the properties of the produced biodiesel are completelyacceptable and meet most of the specifications So it canbe ranked as a realistic fuel and as an alternative to petro-diesel This recommends the applicability of waste mollusksand crabs shells for production of cheap catalyst to producebiodiesel in a cost effective process

The iodine value of the produced biodiesel fuel BDFwas in the range of 105ndash108mg I

2100 g oil Iodine value is a

measure of unsaturation degree The degree of unsaturationgreatly influences fuel oxidation tendency According to EN14214 methyl esters used as diesel fuel must have an iodinevalue less than 120mg I

2100 g sample

The acid value measures the content of free acids in thesample which has influence on fuel aging The acid value ofproduced biodiesel was 06 and 07mgKOHg with averagelowering of asymp80 and 7667 from the used WCO indicatingbetter transesterification efficiency using CaO prepared fromMS than that prepared from CS The TAN of the producedbiodiesel is relatively high but within the ASTM D6751biodiesel standards Candeia et al [23] reported that thebiodiesel with high TAN causes operational problems suchas corrosion and pump plugging caused by corrosion anddeposit formation


Felizardo et al [24] reported that density at 15∘C andkinematic viscosity at 40∘C are important properties mainlyin airless combustion systems because they influence theefficiency of atomization of the fuel flow and distribution

The density of the produced biodiesel fuel usingMS-CaOand CS-CaO recorded 08914 and 09003 gcm3 compared tothat of petro-diesel 08421 gcm3 Fuel with high paraffincityhas high specific gravity and lowAPIThe produced biodieselwas characterized by higher specific gravity (08924 and09011 resp) and lower API value (2706 and 2553 resp)compared to those of the Egyptian petro-diesel sample(08428 and 3639 resp) Therefore volumetrically biodieseldelivers a slightly greater amount of fuel [19]

The viscosity of the produced biodiesel recorded 55 and76 cSt with a remarkable decrease from that of WCO of asymp89and 848 through transesterification using CaO preparedfromMS and CS respectively

The better recorded TAN density and viscosity of theproduced biodiesel using MS-CaO would indicate bettertransesterification efficiency using CaO prepared from MSthan that prepared from CS This might be attributed to therecorded higher basicity of MS-CaO relative to that of CS-CaO

The produced biodiesel has acceptable cold flow prop-erties pour point PP minus2∘C and cloud point 1∘C and ischaracterized by lower CV (3815ndash3555MJkg resp) relevantto that of the Egyptian petro-diesel sample (4549MJkg)

Thewater content of the produced biodiesel is higher thanthat of the Egyptian petro-diesel sample recording 312ndash300and 84 ppm respectively But it is within the recommendablebiodiesel standards lt500 ppm

The produced biodiesel has three major advantages it isultralow sulfur biofuel with sulfur content of 0003ndash0006while petro-diesel has 02 sulfur So it meets the aimof petroleum industry for ultralow sulfur diesel fuel andthe biodiesel combustion will not produce large amount ofsulfur oxides which lead to corrosion of the engine partsand environmental pollution The produced biodiesel has ahigher FP 148ndash143∘C compared to 63∘C for petro-diesel Sobiodiesel is much less flammable fuel than petro-diesel andhence it is much safer in handling storage and transport Inaddition the viscosity of the produced biodiesel 55ndash76 cStis competitive to regular Egyptian standards for petro-diesel16ndash7 cSt Hence no hardware modifications are required forhandling the produced BDF in the existing engine

The better qualifications of the produced biodiesel usingCaO prepared from MS than those of biodiesel producedusing CaO prepared from CS might be attributed to thehigher basicity ofMS-CaO than that of CS-CaOwhich wouldpositively impact the transesterification reaction

4 Conclusion

In the viewpoint of preparation time energy consumptioncost of catalyst and high quality biodiesel yield the CaOcatalyst prepared fromwaste mollusks and crabs shells can berecommended for biodiesel production from waste cookingoil collected from seafood restaurants This would have a

triple positive impact on environment economic and energysectors

Further work is undertaken now in EPR-Biotechnologylaboratory concerning the kinetics and mechanism of thetransesterification process the reusability and stability of theprepared biocatalysts compared to those of the chemical CaOand Novozym 435 and their effects on the biodiesel yield itspurity and quality

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgment

The authors are grateful to Dr Samiha F Deriase Professorof Chemical Engineering in Egyptian Petroleum ResearchInstitute for her help in D-optimal design of experiments

References

[1] N Viriya-empikul P Krasae W Nualpaeng B Yoosuk andK Faungnawakij ldquoBiodiesel production over Ca-based solidcatalysts derived from industrial wastesrdquo Fuel vol 92 no 1 pp239ndash244 2012

[2] P-L Boey G P Maniam and S A Hamid ldquoBiodiesel produc-tion via transesterification of palm olein using waste mud crab(Scylla serrata) shell as a heterogeneous catalystrdquo BioresourceTechnology vol 100 no 24 pp 6362ndash6368 2009

[3] N S El-Gendy S F Deriase and A Hamdy ldquoThe optimizationof biodiesel production from waste frying corn oil using snailsshells as a catalystrdquo Energy Sources Part A Recovery Utilizationand Environmental Effects vol 36 no 6 pp 623ndash637 2014

[4] M Kouzu and J-S Hidaka ldquoTransesterification of vegetable oilinto biodiesel catalyzed by CaO a reviewrdquo Fuel vol 93 pp 1ndash122012

[5] NEl-GendyandHMadianLigno-Cellulosic Biomass for Produc-tion of Bio-Energy in Egypt Lambert Academic SaarbruckenGermany 2013

[6] J Boro A J Thakur and D Deka ldquoSolid oxide derived fromwaste shells of Turbonilla striatula as a renewable catalyst forbiodiesel productionrdquo Fuel Processing Technology vol 92 no10 pp 2061ndash2067 2011

[7] ASTM Standards Methods Annual Book of ASTM StandardsPetroleumProducts and Lubricants (IndashIII) American Society forTesting and Materials West Conshohocken Pa USA 1991

[8] JUS EN 14214 Automotive Fuels Fatty Acid Methyl Esters(FAME) for Diesel Engines-Requirements and Test MethodsStandardization Institute Belgrade Serbia 2004

[9] ASTM Standard D6751 Standard Specification for Bio-DieselFuel (B100) Blend Stock for Distillate Fuels West ConshohockenPA ASTM Automotive Fuels-Fatty-Acid Methyl Esters (FAME)for Diesel EnginesmdashRequirements and Test Methods Beuth-Verlag Berlin Germany 2008

[10] N B Singh and N P Singh ldquoFormation of CaO from thermaldecomposition of calcium carbonate in the presence of car-boxylic acidsrdquo Journal ofThermal Analysis and Calorimetry vol89 no 1 pp 159ndash162 2007

[11] B Engin H Demirtas and M Eken ldquoTemperature effectson egg shells investigated by XRD IR and ESR techniquesrdquo


Radiation Physics and Chemistry vol 75 no 2 pp 268ndash2772006

[12] N Viriya-empikul P Krasae B Puttasawat B Yoosuk NChollacoop and K Faungnawakij ldquoWaste shells of mollusk andegg as biodiesel production catalystsrdquo Bioresource Technologyvol 101 no 10 pp 3765ndash3767 2010

[13] B Yoosuk P Udomsap B Puttasawat and P Krasae ldquoImprov-ing transesterification acitvity of CaO with hydration tech-niquerdquo Bioresource Technology vol 101 no 10 pp 3784ndash37862010

[14] RH Borgwardt ldquoSintering of nascent calciumoxiderdquoChemicalEngineering Science vol 44 no 1 pp 53ndash60 1989

[15] W G Liu N W L Low B Feng G Wang and J C Dinizda Costa ldquoCalcium precursors for the production of CaOsorbents for multicycle CO

2capturerdquo Environmental Science

and Technology vol 44 no 2 pp 841ndash847 2010[16] A Birla B Singh S N Upadhyay and Y C Sharma ldquoKinetics

studies of synthesis of biodiesel from waste frying oil usinga heterogeneous catalyst derived from snail shellrdquo BioresourceTechnology vol 106 pp 95ndash100 2012

[17] W Roschat M Kacha B Yoosuk T Sudyoadsuk and V Pro-marak ldquoBiodiesel production based on heterogeneous processcatalyzed by solid waste coral fragmentrdquo Fuel vol 98 pp 194ndash202 2012

[18] S Hu Y Wang and H Han ldquoUtilization of waste freshwatermussel shell as an economic catalyst for biodiesel productionrdquoBiomass and Bioenergy vol 35 no 8 pp 3627ndash3635 2011

[19] B K Sharma U Rashid F Anwar and S Z Erhan ldquoLubricantproperties of Moringa oil using thermal and tribological tech-niquesrdquo Journal of Thermal Analysis and Calorimetry vol 96no 3 pp 999ndash1008 2009

[20] S M Son K Kusakabe and G Guan ldquoBiodiesel synthesis andproperties from sunflower and waste cooking oils using CaOcatalyst under reflux conditionsrdquo Journal of Applied Sciencesvol 10 no 24 pp 3191ndash3198 2010

[21] L Zhang B Sheng Z Xin Q Liu and S Sun ldquoKineticsof transesterification of palm oil and dimethyl carbonate forbiodiesel production at the catalysis of heterogeneous basecatalystrdquo Bioresource Technology vol 101 no 21 pp 8144ndash81502010

[22] LMCorreiaRMASaboyaN de SousaCampelo et al ldquoChar-acterization of calcium oxide catalysts from natural sourcesand their application in the transesterification of sunflower oilrdquoBioresource Technology vol 151 pp 207ndash213 2014

[23] R A Candeia M C D Silva J R Carvalho Filho et alldquoInfluence of soybean biodiesel content on basic properties ofbiodiesel-diesel blendsrdquo Fuel vol 88 no 4 pp 738ndash743 2009

[24] P Felizardo M J Neiva Correia I Raposo J F Mendes RBerkemeier and J M Bordado ldquoProduction of biodiesel fromwaste frying oilsrdquo Waste Management vol 26 no 5 pp 487ndash494 2006

Submit your manuscripts athttpwwwhindawicom

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CorrosionInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Polymer ScienceInternational Journal of



CeramicsJournal of


CompositesJournal of

NanoparticlesJournal of



International Journal of

Biomaterials


NanoscienceJournal of

TextilesHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of

NanotechnologyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

CrystallographyJournal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


CoatingsJournal of

Advances in

Materials Science and EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Smart Materials Research



MetallurgyJournal of


BioMed Research International

MaterialsJournal of


Nano

materials


Journal ofNanomaterials


In Egypt millions of liters of waste cooking oil WCO arediscarded each year into sewage systems Thus it polluteswater streams causing a lot of waste management problemsand consequently adds to the cost of treating effluent Solidwastes density in Egypt averages about 300 kgm3 where60 is organic wastes [5] Thus production of biodieselfrom WCO using CaO prepared from organic wastes (egeggshells mollusks shells crabs shells etc) would offera triple-fact solution economic environmental and wastemanagement

The aim of this work is to optimize biodiesel trans-esterification process using waste cooking oil and calciumoxide catalyst prepared from waste mollusks and crabs shellscollected from seafood restaurants in an attempt to reach aneffective process for practical low cost industrial biodieselproduction

2 Materials and Methods

21 Materials Pure calcium oxide as heterogeneous catalystandmethanol (ARGrade)were purchased fromFlukaChem-ical Corp Gillingham UK Novozym 435 (Candida antarc-tica Lipase B) was a gift from Novozyme AS BagsvaerdDenmark and was supplied as an immobilized enzymeon macroporous acrylic resin Commercial Egyptian petro-diesel was obtained from a local fuelling station

22 Collection and Preparation of Waste Frying Oil andHeterogeneous Catalyst Thewaste frying oilWFOmollusksand crabs shells (MS and CS) were collected from localseafood restaurants and prepared according to El-Gendy etal [3]

The WCO was characterized by high total acidnumber density and viscosity recording 3mgKOHg oil09208 gcm3 and 50 cSt respectively and its saponificationand iodine value were 197mgKOHg oil and 119mgI

2100 g

oil respectively The WCO consists of asymp2436 3635 2868and 1061 palmitic (C160) stearic (C180) oleic (C181)and linoleic (C182) acid respectively

23 Catalyst Characterization The prepared catalysts werecharacterized according to El-Gendy et al [3] using dif-ferential scanning calorimetric-thermal gravimetric analysis(DSC-TGA) and were performed by Q600 SDT Simul-taneous DSC-TGA (New Castle DE USA) a high-reso-lution X-ray diffractometer (XRD PANalytical XrsquoPert PROMPD Netherland) coupled with Cu k120572 radiation source(120582 = 15418 A) Dispersive Raman spectrometer (BRUKER-SENTERRA Germany) equipped with an integral micro-scope (Olympos) energy dispersive X-ray analysis (EDXOxford X-Max England) conjugated with transmission elec-tron microscope TEM (JEM 2100 Jeol Japan) analyticalFourier transforms infrared (FT-IR Perkin Elmer Spec-trum One USA) instrument scanning electron microscope(SEM JEOL-model JSM-53000 Japan) Particle sizer modelBeckman Coulter Multisizer-3 (Nyon Switzerland) was usedfor determination of particle size distribution The specificsurface area of the prepared biocatalysts was measured byBrunauer-Emmett-Teller BETmethod using low temperature

N2adsorption-desorption (NON A3200e Quantachrome

USA) The samples were tested for pore volume and poresize distribution using Barrett-Joyner-Halenda BJH methodTemperature programmed desorption using CO

2as a probe

molecules (CO2-TPD) was used to study basic properties of

the prepared biocatalysts and it was done according toViriya-empikul et al [1]

24 Transesterification The transesterification reactionswere conducted in a laboratory-scale setup according toEl-Gendy et al [3] and the biodiesel yield was calculatedaccording to Boro et al [6] The activity of the preparedbiocatalysts was compared with that of commerciallyavailable most effective heterogeneous basic chemicalcatalyst CaO and immobilized enzyme Novozym 435

25 Experimental Design and Statistical Analysis Based onD-optimal design of experiments twenty runs of experimentshave been conducted for three levels of four independentvariables methanol oil M O (molar ratio 119860) catalyst con-centration (wt 119861) reaction time (min 119862) and mixingrate (rpm 119863) to study their effect on the yield of theproduced biodiesel at constant temperature 60∘C MATLAB70 software (MathWorks USA) was used for experimentaldesign

Once the experiments were preformed the next stepwas to perform a response surface experiment to producea prediction model to determine curvature detect interac-tions among the design factors (independent variables) andoptimize the process that is to determine the local optimumindependent variables with maximum yield of biodiesel Themodel used in this study to estimate the response surfaceis the quadratic polynomial represented by the followingequation

119884 = 120573119900+

119899

sum

119894=1

120573119894119909119894+

119899minus1

sum

119894=1

119899

sum

119895=119894+1

120573119894119895119909119894119909119895+

119899

sum

119894=1

120573119894119894119909

2

119894 (1)

where 119884 is the biodiesel yield (wt) 119899 is the number offactors 120573

119900is the intercept term 120573

119894 120573119894119895 and 120573

119894119894are the linear

interactive and quadratic coefficients respectively 119909119894rsquos are

the levels of the independent variables (factors) under studyThe statistical software Design Expert 607 (Stat-Ease

Inc Minneapolis USA) was used for regression and graphi-cal analyses of the data obtained and statistical analysis of themodel to evaluate the analysis of variance (ANOVA)

26 PhysicochemicalCharacterization of the ProducedBiodieselTheproduced biodiesel was tested for estimating and evaluat-ing its fuel properties using the standardmethods of analysisfor petroleum products American Society for Testing andMaterials ASTM standards methods [7] The results werecompared with the Egyptian standards for petro-diesel andEuropean andAmerican standards of biodiesel (EN14214 andD-6751 resp) [8 9]

All the properties were analyzed in two replicates and thefinal results given below were obtained as the average values


0

20

40

60

80

100

0 200 400 600 800 1000

Hea

t flow

(Wg

)

Wei

ght l

oss (

)



Mollusks shells

minus6

minus5

minus4

minus3

minus2

minus1

0

Temperature (∘C)

Hea

t flow

(Wg

)

Wei

ght l

oss (

)

Temperature (∘C)

0

20

40

60

80

100

0 200 400 600 800 1000

Crabs shells

minus5

minus45

minus4

minus35

minus3

minus25

minus2

minus15

minus1

minus05

0







3




2(g) (2)









3(JCPDS card






3sdotH2O






10 20 30 40 50 60

Cou

nts

0

500

Chemical CaO


10 20 30 40 50 60

Cou

nts

0200400

0100200

050

050

0400600

0200400

0200400

0200400

0100

1100

1000

900

800

700

600

500

400

Natural

MS


Cou

nts

0200

0200400

0200

0200400

0200400

0200300

0100200

0100200

050

100

1100

1000

900

800

700

600

500

400

Crabs shells

CS















3(asymp48)





3








CS1600

1400

1200

1000

800

600

400

200

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural crabs

700∘C


shells

MS150

100

50

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural mollusks

800∘C


shells


40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

2522

16381617

1471

860621

477

3549

3225

3476

29152848

1786 1082709

6982022

(cmminus1)

T(

)

800∘C

(a)

40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

3236

2030

1637 1420

1083874

619

3468

25091793

2856

3642 1617

1469

1056

4802915 709

1089

(cmminus1)

T(

)700

∘C

(b)


OCOR1

OCOR2O

OndashCndashR3

CH3Ominus

OCOR1

OCOR2Ominus

OndashCndashR3

OCH3

OCOR1

OCOR2

Ominus

R3ndashCndashCH3

O

+


+ CH3Ominus



Scheme 1

















119900= 09590 and 09482 (lt1) and


119900with




1198841= 8243 minus 221119860 minus 098119861 + 312119862 + 080119863 + 448119860

2

+ 189119861

2minus 751119862

2minus 256119863

2minus 266119860119861 minus 116119860119862

+ 579119860119863 + 250119861119862 + 842119861119863 + 087119862119863

(3)


minus 219119860

2+ 463119861

2+ 190119862

2+ 004119863

2+ 489119860119861


(4)

where 1198841and 119884








(a) (b)

(c)

(d)






0 02 04 06 08 1


minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)


A B C D A2 B2 C2 D2


8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)







Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




0

20

40

60

80

100

0 200 400 600 800 1000

Hea

t flow

(Wg

)

Wei

ght l

oss (

)



Mollusks shells

minus6

minus5

minus4

minus3

minus2

minus1

0

Temperature (∘C)

Hea

t flow

(Wg

)

Wei

ght l

oss (

)

Temperature (∘C)

0

20

40

60

80

100

0 200 400 600 800 1000

Crabs shells

minus5

minus45

minus4

minus35

minus3

minus25

minus2

minus15

minus1

minus05

0







3




2(g) (2)









3(JCPDS card






3sdotH2O






10 20 30 40 50 60

Cou

nts

0

500

Chemical CaO


10 20 30 40 50 60

Cou

nts

0200400

0100200

050

050

0400600

0200400

0200400

0200400

0100

1100

1000

900

800

700

600

500

400

Natural

MS


Cou

nts

0200

0200400

0200

0200400

0200400

0200300

0100200

0100200

050

100

1100

1000

900

800

700

600

500

400

Crabs shells

CS















3(asymp48)





3








CS1600

1400

1200

1000

800

600

400

200

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural crabs

700∘C


shells

MS150

100

50

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural mollusks

800∘C


shells


40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

2522

16381617

1471

860621

477

3549

3225

3476

29152848

1786 1082709

6982022

(cmminus1)

T(

)

800∘C

(a)

40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

3236

2030

1637 1420

1083874

619

3468

25091793

2856

3642 1617

1469

1056

4802915 709

1089

(cmminus1)

T(

)700

∘C

(b)


OCOR1

OCOR2O

OndashCndashR3

CH3Ominus

OCOR1

OCOR2Ominus

OndashCndashR3

OCH3

OCOR1

OCOR2

Ominus

R3ndashCndashCH3

O

+


+ CH3Ominus



Scheme 1

















119900= 09590 and 09482 (lt1) and


119900with




1198841= 8243 minus 221119860 minus 098119861 + 312119862 + 080119863 + 448119860

2

+ 189119861

2minus 751119862

2minus 256119863

2minus 266119860119861 minus 116119860119862

+ 579119860119863 + 250119861119862 + 842119861119863 + 087119862119863

(3)


minus 219119860

2+ 463119861

2+ 190119862

2+ 004119863

2+ 489119860119861


(4)

where 1198841and 119884








(a) (b)

(c)

(d)






0 02 04 06 08 1


minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)


A B C D A2 B2 C2 D2


8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)







Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




10 20 30 40 50 60

Cou

nts

0

500

Chemical CaO


10 20 30 40 50 60

Cou

nts

0200400

0100200

050

050

0400600

0200400

0200400

0200400

0100

1100

1000

900

800

700

600

500

400

Natural

MS


Cou

nts

0200

0200400

0200

0200400

0200400

0200300

0100200

0100200

050

100

1100

1000

900

800

700

600

500

400

Crabs shells

CS















3(asymp48)





3








CS1600

1400

1200

1000

800

600

400

200

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural crabs

700∘C


shells

MS150

100

50

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural mollusks

800∘C


shells


40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

2522

16381617

1471

860621

477

3549

3225

3476

29152848

1786 1082709

6982022

(cmminus1)

T(

)

800∘C

(a)

40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

3236

2030

1637 1420

1083874

619

3468

25091793

2856

3642 1617

1469

1056

4802915 709

1089

(cmminus1)

T(

)700

∘C

(b)


OCOR1

OCOR2O

OndashCndashR3

CH3Ominus

OCOR1

OCOR2Ominus

OndashCndashR3

OCH3

OCOR1

OCOR2

Ominus

R3ndashCndashCH3

O

+


+ CH3Ominus



Scheme 1

















119900= 09590 and 09482 (lt1) and


119900with




1198841= 8243 minus 221119860 minus 098119861 + 312119862 + 080119863 + 448119860

2

+ 189119861

2minus 751119862

2minus 256119863

2minus 266119860119861 minus 116119860119862

+ 579119860119863 + 250119861119862 + 842119861119863 + 087119862119863

(3)


minus 219119860

2+ 463119861

2+ 190119862

2+ 004119863

2+ 489119860119861


(4)

where 1198841and 119884








(a) (b)

(c)

(d)






0 02 04 06 08 1


minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)


A B C D A2 B2 C2 D2


8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)







Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




CS1600

1400

1200

1000

800

600

400

200

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural crabs

700∘C


shells

MS150

100

50

0

Ram

an in

tens

ity

200 400 600 800 1000 1200 1400

Natural mollusks

800∘C


shells


40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

2522

16381617

1471

860621

477

3549

3225

3476

29152848

1786 1082709

6982022

(cmminus1)

T(

)

800∘C

(a)

40000 3000 2000 1500 1000 4000100

20304050607080

900


3414

3236

2030

1637 1420

1083874

619

3468

25091793

2856

3642 1617

1469

1056

4802915 709

1089

(cmminus1)

T(

)700

∘C

(b)


OCOR1

OCOR2O

OndashCndashR3

CH3Ominus

OCOR1

OCOR2Ominus

OndashCndashR3

OCH3

OCOR1

OCOR2

Ominus

R3ndashCndashCH3

O

+


+ CH3Ominus



Scheme 1

















119900= 09590 and 09482 (lt1) and


119900with




1198841= 8243 minus 221119860 minus 098119861 + 312119862 + 080119863 + 448119860

2

+ 189119861

2minus 751119862

2minus 256119863

2minus 266119860119861 minus 116119860119862

+ 579119860119863 + 250119861119862 + 842119861119863 + 087119862119863

(3)


minus 219119860

2+ 463119861

2+ 190119862

2+ 004119863

2+ 489119860119861


(4)

where 1198841and 119884








(a) (b)

(c)

(d)






0 02 04 06 08 1


minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)


A B C D A2 B2 C2 D2


8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)







Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials













119900= 09590 and 09482 (lt1) and


119900with




1198841= 8243 minus 221119860 minus 098119861 + 312119862 + 080119863 + 448119860

2

+ 189119861

2minus 751119862

2minus 256119863

2minus 266119860119861 minus 116119860119862

+ 579119860119863 + 250119861119862 + 842119861119863 + 087119862119863

(3)


minus 219119860

2+ 463119861

2+ 190119862

2+ 004119863

2+ 489119860119861


(4)

where 1198841and 119884








(a) (b)

(c)

(d)






0 02 04 06 08 1


minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)


A B C D A2 B2 C2 D2


8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)







Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




(a) (b)

(c)

(d)






0 02 04 06 08 1


minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)


A B C D A2 B2 C2 D2


8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)







Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




0 02 04 06 08 1


minus05

0

05

1

15

2

25

3

35

4

45

PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(a)

0

10

20

30

40

50

60

70

80

0 02 04 06 08 1


PPo

Volu

me a

dsor

ptio

n at

STP

(cm

3g

)

(b)


A B C D A2 B2 C2 D2


8

6

4

2

0

minus2

minus4

minus6

minus8

minus10

AB AC AD BC BD CD

(a)

AB AC AD BC BD CD

Crabs shells CaO

A B C D A2 B2 C2 D2

6

4

2

minus2

minus4

minus6

0

(b)







Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




Table3Ex

perim

entald

esignmatrix

with

experim

entaland

predictedvalues

ofbiod

ieselyield

Run

number

Factorslevels

Biod

ieselyield

(wt

)M

O(M

olar

ratio

)119860

Catalyst(w

t)

119861

Time(min)

119862

Mixingrate(rpm

)119863

CaOfro

mmollusksshells

CaO

from

crabsshells

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Levels

Actual

value

Experim

ental

Predicted

Experim

ental

Predicted

13

121

39

3120

2300

7980

7990

858560

21

61

39

3120

1200

8510

8510

747400

32

91

39

260

340

08700

8700

825

8250

41

61

39

130

2300

7840

7840

855

8550

51

61

26

3120

340

07920

7920

785

7850

62

91

39

130

340

07600

7600

888800

72

91

26

130

2300

7180

7180

929200

83

121

13

130

1200

8340

8340

919085

91

61

13

130

1200

9150

9175

939350

101

61

13

260

2300

8800

8790

925

9290

112

91

26

3120

1200

7380

7380

808000

122

91

13

3120

2300

7840

7840

939300

133

121

13

3120

340

07850

7865

969650

143

121

26

130

340

07840

7840

919100

153

121

26

260

1200

7420

7435

898950

163

121

39

3120

2300

8000

7990

862

8560

171

61

13

130

1200

9200

9175

949350

183

121

26

260

1200

7450

7435

908950

193

121

13

3120

340

07880

7865

979650

201

61

13

260

2300

8780

8790

933

9290


3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




3

Actual

Pred

icte

d

7180

7685

8190

8695

9200

7180 7685 8190 8695 9200

(a)

2

Actual

Pred

icte

d

7400

7975

8550

9125

9700

7400 7975 8550 9125 9700

(b)



Biod

iese

l yie

ld (

)

718

768

819

869

920

A

AB

B

C

CD

D

minus1000 minus0500 0000 0500 1000

(a)


Biod

iese

l yie

ld (

)

740

798

855

913

970

A

A

B

B

C

C

DD

minus1000 minus0500 0000 0500 1000

(b)















2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials













2 1577 1 1577 3105 00026 Significant119862























813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials



















813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


O(a)

813840867893920

Biod

iese

l yie

ld (

)

60

7590

105120

30005250

75009750

12000

Reaction time

M O

(b)

813840867893920

Biod

iese

l yie

ld (

)

6075

90105

120

20002500

30003500

4000

Mixing rate

M O

(c)

813840867893920

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

813840867893920

Biod

iese

l yie

ld (

)

3000

5250

75009750

12000

200025003000

35004000

Reac

tion

time

Mixing rate

(e)

813840867893920

Biod

iese

l yie

ld (

)

30 45 60 75 903000

5250

7500

9750

12000


Reaction time

(f)



795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials




795839882926970

Biod

iese

l yie

ld (

)

6075

90105

120

3045

6075

90


M O

(a)

796839883927970

Biod

iese

l yie

ld (

)

68

911

12

30005250

75009750

12000

Reaction time

M O

(b)

796839883927970

Biod

iese

l yie

ld (

)

6075

90105

120

200250

300350

400

Mixing rate

M O

(c)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

20002500

30003500

4000


Mixing rate

(d)

796839883927970

Biod

iese

l yie

ld (

)

300525

750975

1200

200250

300350

400

Reactio

n time

Mixing rate

(e)

795839882926970

Biod

iese

l yie

ld (

)

3045

6075

90

300525

750975

1200


Reaction time

(f)








BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials







BiodieselEN14214


CaOCrabs shells













2100 g sample











4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials












4 Conclusion






Acknowledgment


References




































CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials



























CeramicsJournal of







Biomaterials




Journal of


Journal of





CoatingsJournal of

Advances in








MaterialsJournal of


Nano

materials



research article an investigation of biodiesel production from...

Documents