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Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent
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Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent Masoud Rahimi∗, Faezeh Mohammadi, Mojdeh Basiri, Mohammad Amin Parsamoghadam, Mohammad Moein Masahi CFD Research Center, Chemical Engineering Department, Razi University, Kermanshah, Iran
a r t i c l e
i n f o
Article history: Received 16 October 2015 Revised 2 March 2016 Accepted 19 April 2016 Available online xxx Keywords: Microreactor Cosolvent Biodiesel production Optimization Response surface methodology
a b s t r a c t In this work, transformation of soybean oil into fatty acid methyl ester (FAME) was studied in different four-way micromixers. Hexane was added to the reaction system as a cosolvent for mass transfer intensification. A three-level-five-factorial Central Composite Design using Response Surface Methodology was employed to optimize the reaction conditions. The main factors affecting the FAME content (wt.%) i.e. reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio and mixer configuration were discussed. The optimum combinations for transesterification to achieve a predicted maximum FAME of 97.67% were found. At this optimum condition, the observed FAME content was found to be 98.8%. The closeness of the experimental results and predicted values demonstrated that the regression model is significant. In the present work, residence time was reduced in an order of seconds (3–15 s), which it has not been fulfilled in the previous works. © 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
1. Introduction With the dwindling of fossil fuel reserves and environmental pollution problems caused by their combustion, the production and application of clean, renewable biofuels is a topic of increasing concern and attention. Biodiesel is an alternative and environmentally friendly fuel and has attracted considerable attentions in recent years [1]. Biodiesel has several advantages over fossil diesel fuel like cetane number, flash point and lubricity characteristics, without any significant difference in heat of combustion between these fuels [2,3]. Biodiesel is commonly produced via a transesterification reaction using alkaline catalyst such as sodium hydroxide (NaOH) or potassium hydroxide (KOH) [4]. In conventional methods of biodiesel production, the reaction is taken places in batch reactors which are usually costly and time consuming and the productivity is relatively low, compared to a continuous process [5]. In order to enhance the physical processes in biodiesel production, such as heat, mass, and momentum transfer, various new types of reactors were suggested. Some of them are microreactors, static mixers, cavitational reactors, oscillatory flow reactors, rotating/spinning tube reactors, microwave reactors, membrane reactors, Ultra-Shear reactors, and Rosett cell reactors. They have been
∗
Corresponding author. Tel.: +98 8314274530; fax: +98 8314274542. E-mail address: [email protected], [email protected] (M. Rahimi).
developed for biodiesel production and the reaction times in these reactors were reduced to 0.3−30 min [6]. Among them, microreactors achieved considerable attention for the increased reaction rates, because of their high mass and heat transfer rates and short molecular diffusion distance. Therefore, higher conversion and selectivity can be obtained in these reactors within a much shorter time compared with batch reactors [7].Several studies on methanolysis using microreactors have recently been published. Table 1 summarizes some of these works [8–10]. Since the oil and alcohol phases in a transesterification system are immiscible, the reaction rate is considerably affected by the mass transfer between two phases. A single phase reaction is suggested by Boocock to improve the mixing of the reactants. The model proposed a cosolvent that makes oil and methanol miscible by reduction of mass transfer resistance [11]. Other researchers have been applied different cosolvents in batch reactors too [12–14]. This work seeks to transesterify soybean oil, employing hexane as the cosolvent. For further improvement, the transesterification reaction was carried out in the micro scale to take the advantages of microchannels simultaneously. The optimum conditions were found for enhancing the biodiesel yield in presence of cosolvent in the studied microreactor. Response Surface Methodology (RSM) was applied to optimize four “numeric” variables i.e. reaction temperature (30–60 °C), residence time (3–15 s), hexane to methanol volumetric ratio (0.1–0.7), oil to methanol volumetric ratio (1–3)
http://dx.doi.org/10.1016/j.jtice.2016.04.023 1876-1070/© 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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M. Rahimi et al. / Journal of the Taiwan Institute of Chemical Engineers 000 (2016) 1–8 Table 1 Comparison between microtube reactors for biodiesel production. Microtube reactor
Temperature (°C)
Methanol to oil molar ratio
Residence time
Catalyst amount
FAME yield (%)
Reference
0.25 mm quartz tube 0.8 mm FEP tube 0.6 mm stainless steel tube
60 60 70
6:1 23.9:1 8:1
5.89 min 100 s 44 s
1% KOH 4.5% KOH 1% KOH
99.4 100 94.8
[8] [9] [10]
Fig. 1. The experimental setup.
and one “categoric” mixer configuration. Finally, experiments were carried out under optimum condition in continuous and batch systems without and in presence of cosolvent. 2. Materials and methods 2.1. Materials The used soybean oil in this study was supplied from Nazgol oil company (Kermanshah, Iran) with an average molecular weight, specific gravity and saponification index of 863.47 g/mol, 910 kg/m3 and 191.88 mg of KOH/g oil, respectively. Methanol (purity> 99.5%), normal hexane (purity> 95%), potassium hydroxide (purities> 85%, pellets) were purchased from Merck Co., Ltd. methyl laurate (methyl dodecanoate, 99.7%) as standard for GC analysis was supplied by Sigma–Aldrich. All materials were employed as received without any further processing. 2.2. Methods and experimental procedure
on a flat plate of poly methyl methacrylate (Plexiglas) by precise milling. Micromixer configurations were used with different confluence angles and inlets as illustrated in Fig. 1. A schematic view of experimental setup is also shown in Fig. 1. The tube was immersed in a temperature-controlled water bath to set the targeted reaction temperature. Three syringe pumps were used to inject the soybean oil, solution of KOH in methanol, and hexane at different flow rates. The residence time was controlled by adjusting the flow rates of three pumps, while the hexane to methanol volumetric ratio and oil to methanol volumetric ratio were controlled by the flow rate ratio of three pumps. It was calculated by dividing the volume of microtube reactor by total fluids flow rate. It should be mentioned that the catalyst concentration in all the experiments, was kept constant at 1 wt.% based on the oil weight. The reaction products were collected at the outlet stream and centrifuged to separate FAMEs part. This part was washed with water three times and dehydrated in an oven at 100 °C for an hour. Then the product was subjected to GC analysis. 2.3. Biodiesel characterization
The transesterification reaction was performed in four-way micromixers with an inner diameter of 0.8 mm and followed by a stainless steel tube with an inner diameter of 1.58 mm. Three different micromixers designed with various confluence angel of 45°, 90° and 135° namely E1, E2 and E3 respectively and fabricated
The samples of biodiesel were analyzed by gas chromatography (Agilent, model 6890 N) with a flame ionization detector (FID).The capillary column was a BPX-70 high polar column. The length, film thickness and internal diameter of the column were 120 m,
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Table 2 Different levels of the selected independent variables in the current study. Variable
Variable symbol
Reaction temperature (°C) Residence time (s) Hexane to methanol volumetric ratio Oil to methanol volumetric ratio Mixer type
A B C D E
Levels −1
0
1
30 3 0.1 1 E1
45 9 0.4 2 E2
60 15 0.7 3 E3
0.25 μm and 0.25 mm, respectively. Nitrogen was used as the carrier gas and also as an auxiliary gas for FID. One microliter of the sample was injected using a 6890 Agilent series injector with a splitless mode. The inlet temperature of sample into injector was 50 °C, which was heated up to 230 °C at a heating rate 5 °C/min. Methyl laurate (C12:0) was added as an internal standard reference into the samples. The FAME was calculated using Eq. (1) as follow [15]:
A
FAME(wt.% ) =
×
As
Ws × 100 W
(1)
where A is the sum of all areas under the curve from C12 to C24, As is the area under the curve of C12:0, Ws is the weight of C12:0 (g) and W is the weight of product (g). 2.4. Experimental design and statistical analysis RSM was used to investigate the influence of reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio, and mixer configuration on the FAME content. Design-Expert (Stat-Ease, trial version) [16] software was used for designing the experiments. A three-level-five-factor Central Composite Design (CCD) was selected and 63 experiments were resulted. The reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio, and mixer configuration were the independent variables in the optimization study of biodiesel production. Table 2 gives the factors and their values. Table 3 describes the experimental design and experiments, which were undertaken in this study. The response variable were analyzed by the multiple regression models. The formulation of the fitted model is given in Eq. (2).
y = β0 +
k i=1
βi xi +
k
βii x2i +
i=1
k k
βi j xi x j
(2)
i=1 j=i+1
where; y is the response, i and j are the linear and quadratic coefficients respectively, xi and xj are the coded variables, β 0 is the regression coefficient, k is the number of factors studied and optimized. Equation was also validated by carrying out confirmatory experiments. 3. Results and discussion Based on the central composite design and results of experiments (Table 3), the quadratic regression model (based on the coded factors) of the experimental data was given as:
FAME(% ) = 83.58159 + 8.774667∗ A + 4.7404∗ B + 1.492823∗C − 3.31805∗ D + 3.916437∗ E [1] − 4.35599∗ E [2] + 6.737608∗ AD − 2.02197∗ AE [1] + 2.150, 833∗ AE [2] − 3.6886∗ BD + 3.621, 655∗ A2 − 4.654, 469∗C 2
(3)
Fig. 2. Model predicted versus measured FAME contents.
where A is the reaction temperature, B is the residence time, C is hexane to methanol volumetric ratio and D is the oil to methanol volumetric ratio respectively. E1 and E2 are the levels of categoric factor (mixer configuration). The model F-value of 52.18 for biodiesel production implied that the model was statistically significant (Table 4). The low p-value (<0.0 0 01) indicates that the model is significant. The correlation coefficient (R2 = 0.9261), adjusted Rsquared (0.9083), predicted R-squared (0.8825) values indicate acceptable correlation between the observed and predicted data. The quadratic regression model was highly significant because of the very low p-value of the F-test and insignificant result of the Lack of Fit model. The Lack of Fit is designed to determine whether the suggested model is adequate to describe the experimental data or not. In the present study, the Lack of Fit F-value of 2.06 confirms that the model is significant. The p-values of the regression coefficients suggest that A, B, C, D, E, AD, AE, BD, A2 and C2 are significant model terms in the study. Therefore, statistical analysis of all the experimental data demonstrated that reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio and mixer configuration had a significant effect on FAME content. It is observed that reaction time with higher coefficient value has more linear effect on FAME content. Biodiesel production was mostly and positively influenced by reaction temperature followed by residence time, E1 mixer, oil to methanol volumetric ratio and hexane to methanol volumetric ratio. The comparison between the predicted and experimental FAME content, given in Fig. 2, shows that the calculated values obtained by model are close enough to the experimental values. 3.1. Effect of transesterification process variables 3.1.1. Effect of reaction parameters on FAME content Temperature is one of the significant factors affecting FAME content. According to Eq. (3), it is observed that reaction temperature exerted more pronounced linear effect because of higher coefficient value. Fig. 3a illustrates the effect of reaction temperature on the FAME content. The reaction temperature is the most important factor, having a positive influence on methyl ester content. By increasing temperature from 30 to 60 °C, FAME increases from 84.37 to 97.87 %. This can be interpreted by a fact that by increase in temperature, the oil viscosity decreases and leads to higher mass transfer between methanol and oil. This can caused the observed increase in
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Table 3 The central composite design and the responses for FAME content. Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
Reaction temperature (°C)
45 60 60 45 45 30 60 30 30 45 60 45 45 30 30 45 30 45 60 45 30 60 45 45 45 30 45 45 45 45 30 45 45 45 45 45 45 60 30 45 45 60 30 45 45 45 60 45 30 45 30 60 45 60 60 45 60 45 45 30 60 30 60
Residence time (s)
9 3 9 9 9 3 3 9 15 9 15 9 9 15 3 9 15 9 15 9 3 3 15 9 9 15 9 3 9 9 3 3 9 9 9 9 9 3 15 9 9 9 3 9 9 9 15 9 3 3 15 15 15 15 15 9 3 9 15 9 3 9 15
Hexane to methanol volumetric ratio
0.4 0.1 0.4 0.4 0.4 0.1 0.7 0.4 0.7 0.4 0.7 0.4 0.1 0.1 0.7 0.4 0.7 0.4 0.7 0.4 0.1 0.7 0.4 0.7 0.4 0.7 0.7 0.4 0.7 0.4 0.7 0.4 0.4 0.1 0.4 0.4 0.4 0.1 0.1 0.4 0.4 0.4 0.7 0.4 0.1 0.4 0.7 0.4 0.1 0.4 0.1 0.1 0.4 0.4 0.1 0.4 0.1 0.4 0.4 0.4 0.7 0.4 0.1
the product yield. Fig. 3b shows the FAME content as a function of residence time. It is seen that the FAME content increased with prolongation of the residence time. The FAME content increased from 82.76 to 92.24% at residence times of 3–15 s. Fig. 3c presents the influence of cosolvent to methanol volumetric ratio on the FAME content. The figure indicates that for this
Oil to methanol volumetric ratio
2 3 2 2 2 1 3 2 3 2 1 2 2 3 1 1 3 2 1 2 1 3 2 2 3 3 2 2 2 1 1 2 2 2 1 2 2 3 3 2 2 2 1 3 2 2 1 2 1 2 3 1 2 2 1 3 3 2 2 2 3 2 1
Mixer type
E3 E2 E2 E1 E3 E3 E1 E3 E2 E2 E1 E2 E1 E2 E1 E1 E1 E2 E3 E2 E1 E2 E3 E1 E2 E3 E2 E3 E3 E3 E2 E1 E3 E3 E2 E3 E2 E1 E3 E1 E1 E1 E3 E3 E2 E1 E2 E1 E2 E2 E1 E3 E1 E3 E2 E1 E3 E3 E2 E1 E3 E2 E1
FAME (%) Experimental
Predicted
84.48 90.30 98.81 90.29 81.60 73.14 95.22 81.77 63.67 77.57 99.85 71.23 81.01 52.02 79.53 88.74 71.67 75.95 95.35 76.50 81.14 92.22 88.52 85.68 75.45 66.67 82.18 77.37 83.18 86.54 71.00 83.37 84.90 80.41 84.74 83.50 71.82 93.30 60.02 86.50 87.90 99.13 78.00 83.45 79.12 88.20 92.35 84.10 66.14 77.37 69.02 95.67 90.52 99.01 92.67 85.45 92.30 85.00 87.52 87.77 93.22 74.77 98.67
84.02 90.00 93.77 87.50 84.02 74.47 97.08 79.00 59.76 79.22 99.72 79.22 81.35 56.77 82.83 90.81 72.20 79.22 98.13 79.22 79.84 92.98 88.76 84.33 75.91 66.83 76.06 79.28 80.86 87.34 70.39 82.76 84.02 77.87 82.54 84.02 79.22 94.09 63.84 87.50 87.50 97.87 77.46 80.70 73.08 87.50 95.62 87.50 67.40 74.48 69.21 95.15 92.24 101.03 92.63 84.18 92.51 84.02 83.96 84.37 95.49 71.92 96.73
investigation, the optimum cosolvent to methanol volume ratio is 0.4 which gives 88% FAME. Further increase in the ratio resulted in the decrease of the FAME content. This could probably be as a result of the dilution of the reactants [14,17]. One other factor affecting the FAME content is molar ratio of alcohol to triglyceride which has been investigated by several
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Table 4 Analysis of variance table for Response Surface Reduced Quadratic model. Source
Sum of squares
df
Mean square
F-Value
p-value
Remarks
Model A-temp B-res time C-Hex/Me D-Oil/Me E-mixer type AD AE BD A2 C2 Residual Lack of Fit Pure error Correlation total
5847.67 461.97 134.83 66.86 330.28 724.63 217.90 87.31 65.31 127.35 210.36 467.05 405.05 62.00 6315.71
12 1 1 1 1 2 1 2 1 1 1 50 38 12 62
487.39 461.97 134.83 66.86 330.28 362.32 217.90 43.66 65.31 127.35 210.36 9.34 10.66 5.17
52.18 49.46 14.43 7.16 35.36 38.79 23.33 4.67 6.99 13.63 22.52
< 0.0 0 01 < 0.0 0 01 0.0 0 04 0.0101 < 0.0 0 01 < 0.0 0 01 < 0.0 0 01 0.0138 0.0109 0.0 0 05 < 0.0 0 01
Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant
2.06
0.0888
Not significant
R2 model = 0.9261; R2 Adj = 0.9083; predicted R2 model = 0.8825.
Fig. 3. Effect of various operational conditions on FAME content.
researchers. Based on the stoichiometric coefficients in transesterification reaction, the reaction between 1 mol triglyceride and 3 mol alcohol produce 3 mol fatty acid ester and 1 mol glycerol. Using excessive alcohol gives more opportunities to reactant molecules to come into contact more efficiently, thereby higher conversion of alkyl esters are obtained in a shorter time. Finally, Fig. 3d shows the effect of the oil to methanol volumetric ratio on the FAME content. The highest FAME content (90.82%) was achieved with a volumetric ratio of 1. However, with a volumetric ratio of 3 a FAME content of 84.18% FAME was achieved.
3.1.2. Effect of micromixer configuration Due to immiscibility between oil and alcohol, the reaction rate of transesterification is limited by mass transfer. The mass-transfer based reaction model for biodiesel synthesis predicts a higher yield of biodiesel with more mixing intensity [18]. Therefore, the biodiesel production in a microreactor is affected by the configuration of micromixer. In this study, three new kinds of four-way micromixers with different confluence angles of 45°, 90° and 135° were employed as previously shown in Fig. 1. The configuration of mixer was
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Fig. 4. Effect of mixer type on biodiesel yield at a reaction temperature 45 °C, residence time of 9 s, hexane to methanol volumetric ratio 0.4 and oil to methanol volumetric ratio 2.
introduced as a variable in the experimental design. With considering this “categoric” factor, experimental runs became 63. Three different kinds of micromixers were examined to see if the confluence angle of the mixer influences the outcome of the transesterification reaction. The obtained results of GC in terms of FAME content demonstrated that the continuous methanolysis was enhanced in E1 mixer followed by E3 and E2, respectively (Fig. 4). From Table 3, the net effect of the mixers can be seen by comparing FAME content of runs 6, 21 and 49.In these conditions by changing the mixer from E2 to E1, 15% increase in the FAME content was obtained. Similar results obtained by comparing runs 11, 19 and 47 showing a 7.5% enhancement. It can be concluded that configuration of the mixer can be an effective parameter and it will be a critical factor especially in unfavorable process conditions. Since it is cheap to construct these configurations of micromixers, it is more economical to improve the FAME content by chosen an appropriate micromixer in comparison with other process variables like temperature, methanol to oil ratio or cosolvent to methanol ratio. 3.2. Interaction between process variables 3.2.1. Effect of reaction temperature and oil to methanol volumetric ratio The effect of reaction temperature and oil to methanol volumetric ratio on biodiesel production at a constant residence time of 9 s and hexane to methanol volumetric ratio of 0.4 in the presence of E1 mixer is presented in Fig. 5a. The results illustrate that FAME content increases with a decrease in oil to methanol volumetric ratio at low temperatures. This can be described with the fact that excess methanol promotes the transesterification reaction and increase the biodiesel yield. However, at higher temperatures, FAME content decreased as oil to methanol volumetric ratio decreased. By referring to Eq. (2), this could be due to a fact that temperature has a higher coefficient value than volumetric oil to methanol ratio. Besides, as far as in equilibrium reactions, the equilibrium constant is influenced by temperature, the FAME content increases by increase in temperature. 3.2.2. Effect of residence time and oil to methanol volumetric ratio Fig. 5b shows effect of interaction of residence time and oil to methanol volumetric ratio on FAME content at a constant temper-
Fig. 5. Response surface plots of the interaction effect of (a) reaction temperature and oil to methanol volumetric ratio (b) residence time and oil to methanol volumetric ratio (c) reaction temperature and mixer configuration on FAME content.
ature of 45 °C and hexane to methanol volumetric ratio 0.4 in the presence of E1 mixer. The FAME content increases at higher time and lower oil to methanol volumetric ratio, because the conversion increases with prolongation of time and excess methanol favors the complete conversion to biodiesel. Therefore interaction between these two variables had a positive significant effect on the FAME content. The FAME increment is less at high oil to methanol volumetric ratios. This may be due to the low residence times in the studied case which made the residence time more significant effect in these conditions. 3.2.3. Effect of reaction temperature and mixer configuration Fig. 5c establishes the interaction of reaction temperature and mixer configuration on the FAME content. The results show that
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Fig. 6. FAME content obtained in batch reactor in the presence and absence of cosolvent.
the highest FAME content was obtained in E1 mixer followed by E3 and E2 at all temperatures. This may be due to fact that hexane is hydrophobic, so it can easily slide between oil molecules and weaken oil-to-oil cohesive forces. On the other hand, vigorous mixing between methanol and cosolvent is not favorable in this system. Therefore, just a mild mixing to reach a convincing homogeneity between them is quite satisfactory for this process. This may be the reason that the best performance among the other mixers was obtained by E1 micromixer. 3.3. Optimization Numerical optimization was used to determine the optimum conditions for increase FAME content. In the optimization of biodiesel production, the goal for temperature, residence time, hexane to methanol volumetric ratio and oil to methanol volumetric ratio was set in range and E1 mixer was selected because of its better performance in comparison with those of other ones. The value of the response was set at maximum value. The optimal conditions of the variables for FAME content estimated by the model equation were as follows: reaction temperature = 57.2 °C, residence time = 9.05 s, hexane to methanol volumetric ratio = 0.45, oil to methanol volumetric ratio = 3, and E1 mixer. An experiment was performed at the optimal conditions to obtain the targeted value of response parameter. Under optimal conditions, the yield of biodiesel reached to 98.8%. The theoretical FAME yield predicted under the above conditions was 97.67%. Predicted response was in good agreement with the experimental results with an error of ± 1%. 3.4. Advantages of using cosolvent in a microreactor over a batch system For demonstrating the effect of hexane on biodiesel production, in the first step, the reaction was carried out in a batch reactor. The reaction was taken placed at a temperature of 57.2 °C and oil to methanol volumetric ratio of 3. Fig. 6. illustrates the FAME content obtained in batch reactor both in the presence and absence of cosolvent. As can be seen in this figure, higher FAME content produced in the presence of cosolvent in much shorter times. This proves that cosolvent can enhanced this transesterification reaction. In the next part, in order to illustrate the advantage of using microscale continuous reactors, transesterification reaction under the obtained optimum conditions was performed in both microreactor and batch reactors. At reaction temperature of 57.2 °C, hexane to methanol volumetric ratio of 0.45 and oil to methanol volumetric ratio of 3, a FAME content of 98.8% was obtained in 9.05 s in the microreactor in the presence of E1 mixer, while the batch
7
process needed 9 min to get the same FAME content. The reaction was performed at similar conditions in the microtube reactor without cosolvent and a FAME content of 84% was obtained in this test. Addition of a cosolvent to the transesterification reaction makes alcohol and triglycride phase miscibile mutually. By increasing the miscibility of the phases, the reaction rate increases due to disappearance of mass transfer resistance between the phases [19]. The transesterification reaction is diffusion-controlled. A slow diffusion of reactants found in two different phases can causes a slow rate. The mixing effect is most significant in the slow rate region of the reaction. One benefit of microreactor is the intensification of the mass transfer. By applying the microreactor technology, mass transfer-controlled regime can be eliminated. Short diffusion distance in microreactors allows the reactant molecules to diffuse quickly through the interface where the reaction is conducted. Therefore, the reaction time is reduced to the order of seconds. The conversion rate is greatly enhanced under these conditions. Residence time was strongly reduced to order of seconds (3– 15 s) in the present work, which it has not been fulfilled in the previous works. Coupling two techniques of microtube and cosolvent leads to these results. 4. Conclusions In this work transesterification of soybean oil was optimized by RSM. Second-order model equation was obtained to predict the biodiesel yield as a function of input parameters. The optimal conditions of the variables were as follows: reaction temperature 57.2 °C, residence time 9.05 s, hexane to methanol volumetric ratio 0.45, oil to methanol volumetric ratio 3 (methanol to oil molar ratio 6), and E1 mixer. Under optimal conditions, the yield of biodiesel reached to 98.8%. Biodiesel production was mostly influenced by reaction temperature followed by residence time, E1 mixer, oil to methanol volumetric ratio and hexane to methanol volumetric ratio. Moreover, it has been found out that using a cosolvent in the microtube reactor leads to the reduction of the reaction time to the order of seconds in the applied microreactor system. Acknowledgments The authors are grateful to Mahidasht Vegetable Oil Company (NAZGOL) for their sincere help during this work. References [1] Rashtizadeh E, Farzaneh F. Transesterification of soybean oil catalyzed by Sr–Ti mixed oxides nanocomposite. J Taiwan Inst Chem Eng 2013;44:917–23. [2] Balat M. Biodiesel fuel from triglycerides via transesterification a review. Energy Sources Part A 20 09;31:130 0–14. [3] Shahbazi MR, Khoshandam B, Nasiri M, Ghazvini M. Biodiesel production via alkali-catalyzed transesterification of Malaysian RBD palm oil – characterization, kinetics model. J Taiwan Inst Chem Eng 2012;43:504–10. [4] Kulkarni MG, Dalai AK. Waste cooking oil an economical source for biodiesel: a review. Ind Eng Chem Res 2006;45:2901–13. [5] Darnoko D, Cheryan M. Kinetics of palm oil transesterification in a batch reactor. J Am Oil Chem Soc 20 0 0;77:1263–7. [6] Qiu Z, Zhao L, Weatherley L. Process intensification technologies in continuous biodiesel production. Chem Eng Process 2010;49:323–30. [7] Kolb G. Review: microstructured reactors for distributed and renewable production of fuels and electrical energy. Chem Eng Process 2013;65:1–44. [8] Sun P, Wang B, Yao J, Zhang L, Xu N. Fast synthesis of biodiesel at high throughput in microstructured reactors. Ind Eng Chem Res 2009;49:1259–64. [9] Sun J, Ju J, Ji L, Zhang L, Xu N. Synthesis of biodiesel in capillary microreactors. Ind Eng Chem Res 2008;47:1398–403. [10] Guan G, Kusakabe K, Moriyama K, Sakurai N. Transesterification of sunflower oil with methanol in a microtube reactor. Ind Eng Chem Res 2009;48:1357–63. [11] Boocock DB, Konar S, Mao V, Lee C, Buligan S. Fast formation of high-purity methyl esters from vegetable oils. J Am Oil Chem Soc 1998;75:1167–72.
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[12] Alhassan Y, Kumar N, Bugaje I, Pali H, Kathkar P. Co-solvents transesterification of cotton seed oil into biodiesel: effects of reaction conditions on quality of fatty acids methyl esters. Energy Convers Manag 2014;84:640–8. [13] Escobar EC, Demafelis RB, Pham LJ, Florece LM, Borines MG. Biodiesel production from Jatropha curcas L. oil by transesterification with hexane as cosolvent. Philipp J Crop Sci 2008;33:1–13. [14] Zhang L, Jin Q, Zhang K, Huang J, Wang X. The Optimization of conversion of waste edible oil to fatty acid methyl esters in homogeneous media. Energy Sources Part A 2012;34:711–19. [15] Wang Y, Ou S, Liu P, Xue F, Tang S. Comparison of two different processes to synthesize biodiesel by waste cooking oil. J Mol Catal A Chem 2006;252:107–12.
[16] Design-Expert-Software. 2015, 24 November. www.statease.com. Trial version. [17] Mohammed-Dabo I, Ahmad M, Hamza A, Muazu K, Aliyu A. Cosolvent transesterification of Jatropha curcas seed oil. J Pet Technol Altern Fuels 2012;3:42–51. [18] Slinn M, Kendall K. Developing the reaction kinetics for a biodiesel reactor. Bioresour Technol 20 09;10 0:2324–7. [19] Guan G, Sakurai N, Kusakabe K. Synthesis of biodiesel from sunflower oil at room temperature in the presence of various cosolvents. Chem Eng J 2009;146:302–6.
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Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent Masoud Rahimi∗, Faezeh Mohammadi, Mojdeh Basiri, Mohammad Amin Parsamoghadam, Mohammad Moein Masahi CFD Research Center, Chemical Engineering Department, Razi University, Kermanshah, Iran
a r t i c l e
i n f o
Article history: Received 16 October 2015 Revised 2 March 2016 Accepted 19 April 2016 Available online xxx Keywords: Microreactor Cosolvent Biodiesel production Optimization Response surface methodology
a b s t r a c t In this work, transformation of soybean oil into fatty acid methyl ester (FAME) was studied in different four-way micromixers. Hexane was added to the reaction system as a cosolvent for mass transfer intensification. A three-level-five-factorial Central Composite Design using Response Surface Methodology was employed to optimize the reaction conditions. The main factors affecting the FAME content (wt.%) i.e. reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio and mixer configuration were discussed. The optimum combinations for transesterification to achieve a predicted maximum FAME of 97.67% were found. At this optimum condition, the observed FAME content was found to be 98.8%. The closeness of the experimental results and predicted values demonstrated that the regression model is significant. In the present work, residence time was reduced in an order of seconds (3–15 s), which it has not been fulfilled in the previous works. © 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
1. Introduction With the dwindling of fossil fuel reserves and environmental pollution problems caused by their combustion, the production and application of clean, renewable biofuels is a topic of increasing concern and attention. Biodiesel is an alternative and environmentally friendly fuel and has attracted considerable attentions in recent years [1]. Biodiesel has several advantages over fossil diesel fuel like cetane number, flash point and lubricity characteristics, without any significant difference in heat of combustion between these fuels [2,3]. Biodiesel is commonly produced via a transesterification reaction using alkaline catalyst such as sodium hydroxide (NaOH) or potassium hydroxide (KOH) [4]. In conventional methods of biodiesel production, the reaction is taken places in batch reactors which are usually costly and time consuming and the productivity is relatively low, compared to a continuous process [5]. In order to enhance the physical processes in biodiesel production, such as heat, mass, and momentum transfer, various new types of reactors were suggested. Some of them are microreactors, static mixers, cavitational reactors, oscillatory flow reactors, rotating/spinning tube reactors, microwave reactors, membrane reactors, Ultra-Shear reactors, and Rosett cell reactors. They have been
∗
Corresponding author. Tel.: +98 8314274530; fax: +98 8314274542. E-mail address: [email protected], [email protected] (M. Rahimi).
developed for biodiesel production and the reaction times in these reactors were reduced to 0.3−30 min [6]. Among them, microreactors achieved considerable attention for the increased reaction rates, because of their high mass and heat transfer rates and short molecular diffusion distance. Therefore, higher conversion and selectivity can be obtained in these reactors within a much shorter time compared with batch reactors [7].Several studies on methanolysis using microreactors have recently been published. Table 1 summarizes some of these works [8–10]. Since the oil and alcohol phases in a transesterification system are immiscible, the reaction rate is considerably affected by the mass transfer between two phases. A single phase reaction is suggested by Boocock to improve the mixing of the reactants. The model proposed a cosolvent that makes oil and methanol miscible by reduction of mass transfer resistance [11]. Other researchers have been applied different cosolvents in batch reactors too [12–14]. This work seeks to transesterify soybean oil, employing hexane as the cosolvent. For further improvement, the transesterification reaction was carried out in the micro scale to take the advantages of microchannels simultaneously. The optimum conditions were found for enhancing the biodiesel yield in presence of cosolvent in the studied microreactor. Response Surface Methodology (RSM) was applied to optimize four “numeric” variables i.e. reaction temperature (30–60 °C), residence time (3–15 s), hexane to methanol volumetric ratio (0.1–0.7), oil to methanol volumetric ratio (1–3)
http://dx.doi.org/10.1016/j.jtice.2016.04.023 1876-1070/© 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
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M. Rahimi et al. / Journal of the Taiwan Institute of Chemical Engineers 000 (2016) 1–8 Table 1 Comparison between microtube reactors for biodiesel production. Microtube reactor
Temperature (°C)
Methanol to oil molar ratio
Residence time
Catalyst amount
FAME yield (%)
Reference
0.25 mm quartz tube 0.8 mm FEP tube 0.6 mm stainless steel tube
60 60 70
6:1 23.9:1 8:1
5.89 min 100 s 44 s
1% KOH 4.5% KOH 1% KOH
99.4 100 94.8
[8] [9] [10]
Fig. 1. The experimental setup.
and one “categoric” mixer configuration. Finally, experiments were carried out under optimum condition in continuous and batch systems without and in presence of cosolvent. 2. Materials and methods 2.1. Materials The used soybean oil in this study was supplied from Nazgol oil company (Kermanshah, Iran) with an average molecular weight, specific gravity and saponification index of 863.47 g/mol, 910 kg/m3 and 191.88 mg of KOH/g oil, respectively. Methanol (purity> 99.5%), normal hexane (purity> 95%), potassium hydroxide (purities> 85%, pellets) were purchased from Merck Co., Ltd. methyl laurate (methyl dodecanoate, 99.7%) as standard for GC analysis was supplied by Sigma–Aldrich. All materials were employed as received without any further processing. 2.2. Methods and experimental procedure
on a flat plate of poly methyl methacrylate (Plexiglas) by precise milling. Micromixer configurations were used with different confluence angles and inlets as illustrated in Fig. 1. A schematic view of experimental setup is also shown in Fig. 1. The tube was immersed in a temperature-controlled water bath to set the targeted reaction temperature. Three syringe pumps were used to inject the soybean oil, solution of KOH in methanol, and hexane at different flow rates. The residence time was controlled by adjusting the flow rates of three pumps, while the hexane to methanol volumetric ratio and oil to methanol volumetric ratio were controlled by the flow rate ratio of three pumps. It was calculated by dividing the volume of microtube reactor by total fluids flow rate. It should be mentioned that the catalyst concentration in all the experiments, was kept constant at 1 wt.% based on the oil weight. The reaction products were collected at the outlet stream and centrifuged to separate FAMEs part. This part was washed with water three times and dehydrated in an oven at 100 °C for an hour. Then the product was subjected to GC analysis. 2.3. Biodiesel characterization
The transesterification reaction was performed in four-way micromixers with an inner diameter of 0.8 mm and followed by a stainless steel tube with an inner diameter of 1.58 mm. Three different micromixers designed with various confluence angel of 45°, 90° and 135° namely E1, E2 and E3 respectively and fabricated
The samples of biodiesel were analyzed by gas chromatography (Agilent, model 6890 N) with a flame ionization detector (FID).The capillary column was a BPX-70 high polar column. The length, film thickness and internal diameter of the column were 120 m,
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Table 2 Different levels of the selected independent variables in the current study. Variable
Variable symbol
Reaction temperature (°C) Residence time (s) Hexane to methanol volumetric ratio Oil to methanol volumetric ratio Mixer type
A B C D E
Levels −1
0
1
30 3 0.1 1 E1
45 9 0.4 2 E2
60 15 0.7 3 E3
0.25 μm and 0.25 mm, respectively. Nitrogen was used as the carrier gas and also as an auxiliary gas for FID. One microliter of the sample was injected using a 6890 Agilent series injector with a splitless mode. The inlet temperature of sample into injector was 50 °C, which was heated up to 230 °C at a heating rate 5 °C/min. Methyl laurate (C12:0) was added as an internal standard reference into the samples. The FAME was calculated using Eq. (1) as follow [15]:
A
FAME(wt.% ) =
×
As
Ws × 100 W
(1)
where A is the sum of all areas under the curve from C12 to C24, As is the area under the curve of C12:0, Ws is the weight of C12:0 (g) and W is the weight of product (g). 2.4. Experimental design and statistical analysis RSM was used to investigate the influence of reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio, and mixer configuration on the FAME content. Design-Expert (Stat-Ease, trial version) [16] software was used for designing the experiments. A three-level-five-factor Central Composite Design (CCD) was selected and 63 experiments were resulted. The reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio, and mixer configuration were the independent variables in the optimization study of biodiesel production. Table 2 gives the factors and their values. Table 3 describes the experimental design and experiments, which were undertaken in this study. The response variable were analyzed by the multiple regression models. The formulation of the fitted model is given in Eq. (2).
y = β0 +
k i=1
βi xi +
k
βii x2i +
i=1
k k
βi j xi x j
(2)
i=1 j=i+1
where; y is the response, i and j are the linear and quadratic coefficients respectively, xi and xj are the coded variables, β 0 is the regression coefficient, k is the number of factors studied and optimized. Equation was also validated by carrying out confirmatory experiments. 3. Results and discussion Based on the central composite design and results of experiments (Table 3), the quadratic regression model (based on the coded factors) of the experimental data was given as:
FAME(% ) = 83.58159 + 8.774667∗ A + 4.7404∗ B + 1.492823∗C − 3.31805∗ D + 3.916437∗ E [1] − 4.35599∗ E [2] + 6.737608∗ AD − 2.02197∗ AE [1] + 2.150, 833∗ AE [2] − 3.6886∗ BD + 3.621, 655∗ A2 − 4.654, 469∗C 2
(3)
Fig. 2. Model predicted versus measured FAME contents.
where A is the reaction temperature, B is the residence time, C is hexane to methanol volumetric ratio and D is the oil to methanol volumetric ratio respectively. E1 and E2 are the levels of categoric factor (mixer configuration). The model F-value of 52.18 for biodiesel production implied that the model was statistically significant (Table 4). The low p-value (<0.0 0 01) indicates that the model is significant. The correlation coefficient (R2 = 0.9261), adjusted Rsquared (0.9083), predicted R-squared (0.8825) values indicate acceptable correlation between the observed and predicted data. The quadratic regression model was highly significant because of the very low p-value of the F-test and insignificant result of the Lack of Fit model. The Lack of Fit is designed to determine whether the suggested model is adequate to describe the experimental data or not. In the present study, the Lack of Fit F-value of 2.06 confirms that the model is significant. The p-values of the regression coefficients suggest that A, B, C, D, E, AD, AE, BD, A2 and C2 are significant model terms in the study. Therefore, statistical analysis of all the experimental data demonstrated that reaction temperature, residence time, hexane to methanol volumetric ratio, oil to methanol volumetric ratio and mixer configuration had a significant effect on FAME content. It is observed that reaction time with higher coefficient value has more linear effect on FAME content. Biodiesel production was mostly and positively influenced by reaction temperature followed by residence time, E1 mixer, oil to methanol volumetric ratio and hexane to methanol volumetric ratio. The comparison between the predicted and experimental FAME content, given in Fig. 2, shows that the calculated values obtained by model are close enough to the experimental values. 3.1. Effect of transesterification process variables 3.1.1. Effect of reaction parameters on FAME content Temperature is one of the significant factors affecting FAME content. According to Eq. (3), it is observed that reaction temperature exerted more pronounced linear effect because of higher coefficient value. Fig. 3a illustrates the effect of reaction temperature on the FAME content. The reaction temperature is the most important factor, having a positive influence on methyl ester content. By increasing temperature from 30 to 60 °C, FAME increases from 84.37 to 97.87 %. This can be interpreted by a fact that by increase in temperature, the oil viscosity decreases and leads to higher mass transfer between methanol and oil. This can caused the observed increase in
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Table 3 The central composite design and the responses for FAME content. Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63
Reaction temperature (°C)
45 60 60 45 45 30 60 30 30 45 60 45 45 30 30 45 30 45 60 45 30 60 45 45 45 30 45 45 45 45 30 45 45 45 45 45 45 60 30 45 45 60 30 45 45 45 60 45 30 45 30 60 45 60 60 45 60 45 45 30 60 30 60
Residence time (s)
9 3 9 9 9 3 3 9 15 9 15 9 9 15 3 9 15 9 15 9 3 3 15 9 9 15 9 3 9 9 3 3 9 9 9 9 9 3 15 9 9 9 3 9 9 9 15 9 3 3 15 15 15 15 15 9 3 9 15 9 3 9 15
Hexane to methanol volumetric ratio
0.4 0.1 0.4 0.4 0.4 0.1 0.7 0.4 0.7 0.4 0.7 0.4 0.1 0.1 0.7 0.4 0.7 0.4 0.7 0.4 0.1 0.7 0.4 0.7 0.4 0.7 0.7 0.4 0.7 0.4 0.7 0.4 0.4 0.1 0.4 0.4 0.4 0.1 0.1 0.4 0.4 0.4 0.7 0.4 0.1 0.4 0.7 0.4 0.1 0.4 0.1 0.1 0.4 0.4 0.1 0.4 0.1 0.4 0.4 0.4 0.7 0.4 0.1
the product yield. Fig. 3b shows the FAME content as a function of residence time. It is seen that the FAME content increased with prolongation of the residence time. The FAME content increased from 82.76 to 92.24% at residence times of 3–15 s. Fig. 3c presents the influence of cosolvent to methanol volumetric ratio on the FAME content. The figure indicates that for this
Oil to methanol volumetric ratio
2 3 2 2 2 1 3 2 3 2 1 2 2 3 1 1 3 2 1 2 1 3 2 2 3 3 2 2 2 1 1 2 2 2 1 2 2 3 3 2 2 2 1 3 2 2 1 2 1 2 3 1 2 2 1 3 3 2 2 2 3 2 1
Mixer type
E3 E2 E2 E1 E3 E3 E1 E3 E2 E2 E1 E2 E1 E2 E1 E1 E1 E2 E3 E2 E1 E2 E3 E1 E2 E3 E2 E3 E3 E3 E2 E1 E3 E3 E2 E3 E2 E1 E3 E1 E1 E1 E3 E3 E2 E1 E2 E1 E2 E2 E1 E3 E1 E3 E2 E1 E3 E3 E2 E1 E3 E2 E1
FAME (%) Experimental
Predicted
84.48 90.30 98.81 90.29 81.60 73.14 95.22 81.77 63.67 77.57 99.85 71.23 81.01 52.02 79.53 88.74 71.67 75.95 95.35 76.50 81.14 92.22 88.52 85.68 75.45 66.67 82.18 77.37 83.18 86.54 71.00 83.37 84.90 80.41 84.74 83.50 71.82 93.30 60.02 86.50 87.90 99.13 78.00 83.45 79.12 88.20 92.35 84.10 66.14 77.37 69.02 95.67 90.52 99.01 92.67 85.45 92.30 85.00 87.52 87.77 93.22 74.77 98.67
84.02 90.00 93.77 87.50 84.02 74.47 97.08 79.00 59.76 79.22 99.72 79.22 81.35 56.77 82.83 90.81 72.20 79.22 98.13 79.22 79.84 92.98 88.76 84.33 75.91 66.83 76.06 79.28 80.86 87.34 70.39 82.76 84.02 77.87 82.54 84.02 79.22 94.09 63.84 87.50 87.50 97.87 77.46 80.70 73.08 87.50 95.62 87.50 67.40 74.48 69.21 95.15 92.24 101.03 92.63 84.18 92.51 84.02 83.96 84.37 95.49 71.92 96.73
investigation, the optimum cosolvent to methanol volume ratio is 0.4 which gives 88% FAME. Further increase in the ratio resulted in the decrease of the FAME content. This could probably be as a result of the dilution of the reactants [14,17]. One other factor affecting the FAME content is molar ratio of alcohol to triglyceride which has been investigated by several
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Table 4 Analysis of variance table for Response Surface Reduced Quadratic model. Source
Sum of squares
df
Mean square
F-Value
p-value
Remarks
Model A-temp B-res time C-Hex/Me D-Oil/Me E-mixer type AD AE BD A2 C2 Residual Lack of Fit Pure error Correlation total
5847.67 461.97 134.83 66.86 330.28 724.63 217.90 87.31 65.31 127.35 210.36 467.05 405.05 62.00 6315.71
12 1 1 1 1 2 1 2 1 1 1 50 38 12 62
487.39 461.97 134.83 66.86 330.28 362.32 217.90 43.66 65.31 127.35 210.36 9.34 10.66 5.17
52.18 49.46 14.43 7.16 35.36 38.79 23.33 4.67 6.99 13.63 22.52
< 0.0 0 01 < 0.0 0 01 0.0 0 04 0.0101 < 0.0 0 01 < 0.0 0 01 < 0.0 0 01 0.0138 0.0109 0.0 0 05 < 0.0 0 01
Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant
2.06
0.0888
Not significant
R2 model = 0.9261; R2 Adj = 0.9083; predicted R2 model = 0.8825.
Fig. 3. Effect of various operational conditions on FAME content.
researchers. Based on the stoichiometric coefficients in transesterification reaction, the reaction between 1 mol triglyceride and 3 mol alcohol produce 3 mol fatty acid ester and 1 mol glycerol. Using excessive alcohol gives more opportunities to reactant molecules to come into contact more efficiently, thereby higher conversion of alkyl esters are obtained in a shorter time. Finally, Fig. 3d shows the effect of the oil to methanol volumetric ratio on the FAME content. The highest FAME content (90.82%) was achieved with a volumetric ratio of 1. However, with a volumetric ratio of 3 a FAME content of 84.18% FAME was achieved.
3.1.2. Effect of micromixer configuration Due to immiscibility between oil and alcohol, the reaction rate of transesterification is limited by mass transfer. The mass-transfer based reaction model for biodiesel synthesis predicts a higher yield of biodiesel with more mixing intensity [18]. Therefore, the biodiesel production in a microreactor is affected by the configuration of micromixer. In this study, three new kinds of four-way micromixers with different confluence angles of 45°, 90° and 135° were employed as previously shown in Fig. 1. The configuration of mixer was
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Fig. 4. Effect of mixer type on biodiesel yield at a reaction temperature 45 °C, residence time of 9 s, hexane to methanol volumetric ratio 0.4 and oil to methanol volumetric ratio 2.
introduced as a variable in the experimental design. With considering this “categoric” factor, experimental runs became 63. Three different kinds of micromixers were examined to see if the confluence angle of the mixer influences the outcome of the transesterification reaction. The obtained results of GC in terms of FAME content demonstrated that the continuous methanolysis was enhanced in E1 mixer followed by E3 and E2, respectively (Fig. 4). From Table 3, the net effect of the mixers can be seen by comparing FAME content of runs 6, 21 and 49.In these conditions by changing the mixer from E2 to E1, 15% increase in the FAME content was obtained. Similar results obtained by comparing runs 11, 19 and 47 showing a 7.5% enhancement. It can be concluded that configuration of the mixer can be an effective parameter and it will be a critical factor especially in unfavorable process conditions. Since it is cheap to construct these configurations of micromixers, it is more economical to improve the FAME content by chosen an appropriate micromixer in comparison with other process variables like temperature, methanol to oil ratio or cosolvent to methanol ratio. 3.2. Interaction between process variables 3.2.1. Effect of reaction temperature and oil to methanol volumetric ratio The effect of reaction temperature and oil to methanol volumetric ratio on biodiesel production at a constant residence time of 9 s and hexane to methanol volumetric ratio of 0.4 in the presence of E1 mixer is presented in Fig. 5a. The results illustrate that FAME content increases with a decrease in oil to methanol volumetric ratio at low temperatures. This can be described with the fact that excess methanol promotes the transesterification reaction and increase the biodiesel yield. However, at higher temperatures, FAME content decreased as oil to methanol volumetric ratio decreased. By referring to Eq. (2), this could be due to a fact that temperature has a higher coefficient value than volumetric oil to methanol ratio. Besides, as far as in equilibrium reactions, the equilibrium constant is influenced by temperature, the FAME content increases by increase in temperature. 3.2.2. Effect of residence time and oil to methanol volumetric ratio Fig. 5b shows effect of interaction of residence time and oil to methanol volumetric ratio on FAME content at a constant temper-
Fig. 5. Response surface plots of the interaction effect of (a) reaction temperature and oil to methanol volumetric ratio (b) residence time and oil to methanol volumetric ratio (c) reaction temperature and mixer configuration on FAME content.
ature of 45 °C and hexane to methanol volumetric ratio 0.4 in the presence of E1 mixer. The FAME content increases at higher time and lower oil to methanol volumetric ratio, because the conversion increases with prolongation of time and excess methanol favors the complete conversion to biodiesel. Therefore interaction between these two variables had a positive significant effect on the FAME content. The FAME increment is less at high oil to methanol volumetric ratios. This may be due to the low residence times in the studied case which made the residence time more significant effect in these conditions. 3.2.3. Effect of reaction temperature and mixer configuration Fig. 5c establishes the interaction of reaction temperature and mixer configuration on the FAME content. The results show that
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Fig. 6. FAME content obtained in batch reactor in the presence and absence of cosolvent.
the highest FAME content was obtained in E1 mixer followed by E3 and E2 at all temperatures. This may be due to fact that hexane is hydrophobic, so it can easily slide between oil molecules and weaken oil-to-oil cohesive forces. On the other hand, vigorous mixing between methanol and cosolvent is not favorable in this system. Therefore, just a mild mixing to reach a convincing homogeneity between them is quite satisfactory for this process. This may be the reason that the best performance among the other mixers was obtained by E1 micromixer. 3.3. Optimization Numerical optimization was used to determine the optimum conditions for increase FAME content. In the optimization of biodiesel production, the goal for temperature, residence time, hexane to methanol volumetric ratio and oil to methanol volumetric ratio was set in range and E1 mixer was selected because of its better performance in comparison with those of other ones. The value of the response was set at maximum value. The optimal conditions of the variables for FAME content estimated by the model equation were as follows: reaction temperature = 57.2 °C, residence time = 9.05 s, hexane to methanol volumetric ratio = 0.45, oil to methanol volumetric ratio = 3, and E1 mixer. An experiment was performed at the optimal conditions to obtain the targeted value of response parameter. Under optimal conditions, the yield of biodiesel reached to 98.8%. The theoretical FAME yield predicted under the above conditions was 97.67%. Predicted response was in good agreement with the experimental results with an error of ± 1%. 3.4. Advantages of using cosolvent in a microreactor over a batch system For demonstrating the effect of hexane on biodiesel production, in the first step, the reaction was carried out in a batch reactor. The reaction was taken placed at a temperature of 57.2 °C and oil to methanol volumetric ratio of 3. Fig. 6. illustrates the FAME content obtained in batch reactor both in the presence and absence of cosolvent. As can be seen in this figure, higher FAME content produced in the presence of cosolvent in much shorter times. This proves that cosolvent can enhanced this transesterification reaction. In the next part, in order to illustrate the advantage of using microscale continuous reactors, transesterification reaction under the obtained optimum conditions was performed in both microreactor and batch reactors. At reaction temperature of 57.2 °C, hexane to methanol volumetric ratio of 0.45 and oil to methanol volumetric ratio of 3, a FAME content of 98.8% was obtained in 9.05 s in the microreactor in the presence of E1 mixer, while the batch
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process needed 9 min to get the same FAME content. The reaction was performed at similar conditions in the microtube reactor without cosolvent and a FAME content of 84% was obtained in this test. Addition of a cosolvent to the transesterification reaction makes alcohol and triglycride phase miscibile mutually. By increasing the miscibility of the phases, the reaction rate increases due to disappearance of mass transfer resistance between the phases [19]. The transesterification reaction is diffusion-controlled. A slow diffusion of reactants found in two different phases can causes a slow rate. The mixing effect is most significant in the slow rate region of the reaction. One benefit of microreactor is the intensification of the mass transfer. By applying the microreactor technology, mass transfer-controlled regime can be eliminated. Short diffusion distance in microreactors allows the reactant molecules to diffuse quickly through the interface where the reaction is conducted. Therefore, the reaction time is reduced to the order of seconds. The conversion rate is greatly enhanced under these conditions. Residence time was strongly reduced to order of seconds (3– 15 s) in the present work, which it has not been fulfilled in the previous works. Coupling two techniques of microtube and cosolvent leads to these results. 4. Conclusions In this work transesterification of soybean oil was optimized by RSM. Second-order model equation was obtained to predict the biodiesel yield as a function of input parameters. The optimal conditions of the variables were as follows: reaction temperature 57.2 °C, residence time 9.05 s, hexane to methanol volumetric ratio 0.45, oil to methanol volumetric ratio 3 (methanol to oil molar ratio 6), and E1 mixer. Under optimal conditions, the yield of biodiesel reached to 98.8%. Biodiesel production was mostly influenced by reaction temperature followed by residence time, E1 mixer, oil to methanol volumetric ratio and hexane to methanol volumetric ratio. Moreover, it has been found out that using a cosolvent in the microtube reactor leads to the reduction of the reaction time to the order of seconds in the applied microreactor system. Acknowledgments The authors are grateful to Mahidasht Vegetable Oil Company (NAZGOL) for their sincere help during this work. References [1] Rashtizadeh E, Farzaneh F. Transesterification of soybean oil catalyzed by Sr–Ti mixed oxides nanocomposite. J Taiwan Inst Chem Eng 2013;44:917–23. [2] Balat M. Biodiesel fuel from triglycerides via transesterification a review. Energy Sources Part A 20 09;31:130 0–14. [3] Shahbazi MR, Khoshandam B, Nasiri M, Ghazvini M. Biodiesel production via alkali-catalyzed transesterification of Malaysian RBD palm oil – characterization, kinetics model. J Taiwan Inst Chem Eng 2012;43:504–10. [4] Kulkarni MG, Dalai AK. Waste cooking oil an economical source for biodiesel: a review. Ind Eng Chem Res 2006;45:2901–13. [5] Darnoko D, Cheryan M. Kinetics of palm oil transesterification in a batch reactor. J Am Oil Chem Soc 20 0 0;77:1263–7. [6] Qiu Z, Zhao L, Weatherley L. Process intensification technologies in continuous biodiesel production. Chem Eng Process 2010;49:323–30. [7] Kolb G. Review: microstructured reactors for distributed and renewable production of fuels and electrical energy. Chem Eng Process 2013;65:1–44. [8] Sun P, Wang B, Yao J, Zhang L, Xu N. Fast synthesis of biodiesel at high throughput in microstructured reactors. Ind Eng Chem Res 2009;49:1259–64. [9] Sun J, Ju J, Ji L, Zhang L, Xu N. Synthesis of biodiesel in capillary microreactors. Ind Eng Chem Res 2008;47:1398–403. [10] Guan G, Kusakabe K, Moriyama K, Sakurai N. Transesterification of sunflower oil with methanol in a microtube reactor. Ind Eng Chem Res 2009;48:1357–63. [11] Boocock DB, Konar S, Mao V, Lee C, Buligan S. Fast formation of high-purity methyl esters from vegetable oils. J Am Oil Chem Soc 1998;75:1167–72.
Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023
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Please cite this article as: M. Rahimi et al., Transesterification of soybean oil in four-way micromixers for biodiesel production using a cosolvent, Journal of the Taiwan Institute of Chemical Engineers (2016), http://dx.doi.org/10.1016/j.jtice.2016.04.023