5.2
Impact Factor
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Search in posts
Search in pages
Filter by Categories
Corrigendum
Current Issue
Editorial
Erratum
Full Length Article
Full lenth article
Letter to Editor
Original Article
Research article
Retraction
Retraction notice
Review
Review Article
SPECIAL ISSUE: ENVIRONMENTAL CHEMISTRY
5.3
Impact Factor
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Search in posts
Search in pages
Filter by Categories
Corrigendum
Current Issue
Editorial
Erratum
Full Length Article
Full lenth article
Letter to Editor
Original Article
Research article
Retraction
Retraction notice
Review
Review Article
SPECIAL ISSUE: ENVIRONMENTAL CHEMISTRY
View/Download PDF

Translate this page into:

Original article
12 (
8
); 2028-2036
doi:
10.1016/j.arabjc.2014.12.034

Statistical optimization of biodiesel production from para rubber seed oil by SO3H-MCM-41 catalyst

Department of Chemistry, Faculty of Science and Technology, Thammasat University, Pathum Thani 12120, Thailand
Chemical Engineering Division, Faculty of Engineering, Rajamangala University of Technology Krungthep, Bangkok 10120, Thailand
Department of Chemical Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
The Institute of Biotechnology and Genetic Engineering, Chulalongkorn University, Bangkok 10330, Thailand
Department of Chemical Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand

⁎Corresponding author. Tel.: +66 25644440x2418; fax: +66 25644483. chanatip@tu.ac.th (Chanatip Samart)

Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Peer review under responsibility of King Saud University.

Abstract

The experimental parameters for biodiesel production from para rubber seed oil and methanol using a SO3H-MCM-41 catalyst were optimized statistically. The SO3H-MCM-41 catalyst was synthesized by co-condensation in the presence of tetraethyl orthosilicate, 3-mercaptopropyl (methyl) dimethoxysilane (MPMDS) and cetyl-trimethylammonium bromide. In the last step, the solid catalyst (SH-MCM41) was oxidized by H2O2 to SO3H-MCM-41. The acid capacity of the obtained SO3H-MCM-41 catalyst was quantified by back titration with 0.1 M sodium hydroxide. The physical and chemical properties of the SO3H-MCM-41 were characterized by nitrogen adsorption/desorption, X-ray diffractometry, Fourier transform infrared spectroscopy and thermogravimetric analysis. The effect of varying the catalyst loading (wt.%), reaction time (h) and temperature (°C) and molar composition of MPMDS on the biodiesel yield were investigated using a 2k factorial design. The optimal conditions to maximize the biodiesel yield, obtained from the response surface analysis using a Box–Behnken design, was a 14.5 wt.% catalyst loading, and a reaction time and temperature of 48 h and 129.6 °C. Under these conditions a fatty acid methyl ester (biodiesel) yield of 84% was predicted, and an 83.10 ± 0.39% yield experimentally obtained.

Keywords

Para rubber seed oil
Biodiesel
SO3H-MCM-41
2k factorial design
Box–Behnken design
1

1 Introduction

Owing to the increasing price of petroleum, its diminishing non-renewable reserve status and its limited geopolitical distribution coupled with the environmental concerns involved with the increasing global population number and socioeconomics (leading to an increasing demand for energy and food production), more sustainable and renewable green energy alternatives are required. Biodiesel is one such potential alternative fuel, which could be used as a partial petroleum diesel replacement as it is theoretically a renewable, non-toxic and biodegradable diesel fuel (Knothe, 2010). Generally, biodiesel can be produced from renewable resources, such as vegetable oils and animal fats, via esterification and transesterification with small chain alcohols, principally methanol or ethanol. Economically and ethically, edible oils (such as palm oil, soybean oil, and sun flower oil) are not suitable because they compete with and affect the supply chain of food industries. Therefore, non-edible oils are more appropriate raw materials for biodiesel production (Atadashi et al., 2013; Gerpen, 2005; Campanelli et al., 2010). Recently para rubber seed oil (RSO), which is largely inedible due to its cyanogenic glycosides, was shown to be rich is suitable fatty acid esters for biodiesel production (palmitic C16:0 10.2%, stearic C18:0 8.7%, oleic C18:1 24.6%, linoleic C18:2 39.6%, and linolenic C18:3 16.3%). The seeds are not utilized in rubber production but are produced in large annual amounts from rubber tree cultivations and mostly go to waste, while oil extraction does not compete with their use for animal feeds as the residual seed cake after oil extraction is suitable for animal feeds. Because the top three global crude rubber producers are Thailand, Indonesia and Malaysia, RSO is then a challenging raw material for biodiesel production, especially in southeast Asian countries. However, RSO contains a high free fatty acid (FFA) content, which causes problems with alkali catalyst mediated transesterification due to soap formation (Atadashi et al., 2013; Gerpen, 2005). Acid catalysts have been selected to simultaneously catalyze the esterification and transesterification of high FFA containing oils. Normally, the commercialized biodiesel production process uses homogeneous catalysts (Ramadhas et al., 2005; Serio et al., 2005; Agarwal et al., 2012), but it produces a large amount of contaminated wastewater due to removal of the remaining catalyst and partial solubility of the biodiesel in the wastewater (especially alkaline wastewater). Moreover, the homogeneous catalysts are difficult to recover or reuse. The supercritical fluid or non-catalytic process can resolve the wastewater problem but has a high construction cost (Demirbas, 2005; Manuale et al., 2011). Heterogeneous catalysts, however, do not suffer from these problems (Chouhan and Sarma, 2011; Endalew et al., 2011; Puna et al., 2010; Kawashima et al., 2008; Samart et al., 2009; Karimi et al., 2012).

Heterogeneous acid catalysts have shown a high catalytic activity in both the esterification of FFA and transesterification of fats and oils to fatty acid alkyl esters (biodiesel). However, many types of acid catalysts, such as ferric alginate beads (Lim et al., 2013), aminophosphonic acid resin D418 (Yin et al., 2012), N-propyl sulfamic acid MCM-41 (Xie and Yang, 2011), acid activated carbon (Shu et al., 2009; Shu et al., 2010) and sulfonic acid MCM-41 (Díaz et al., 2003), have been selected and investigated for the esterification reaction alone. On the other hand, heterogeneous catalysts that can be used to simultaneously catalyze esterification and transesterification reactions are of great interest.

In this work, biodiesel (as fatty acid methyl esters; FAME) was produced from RSO and methanol using sulfonic acid containing MCM-41 (SO3H-MCM-41) as an acid heterogeneous catalyst. Biodiesel production under various conditions was investigated to find the more optimal (effective) variables at a 95% confidence level using a 2k factorial based experimental design (Berrios et al., 2009) with the suitable condition being optimized by the Box–Behnken design (Yin et al., 2012; Zhang et al., 2010; Charoenchaitrakool and Thienmethangkoon, 2011).

2

2 Experimental

2.1

2.1 Synthesis of SO3H-MCM-41 catalyst

A combination of alkyl- and mercaptopropyl-functionalized MCM-41 was synthesized via the one-step co-condensation of Tetraethyl orthosilicate (TEOS, 99% Aldrich) and 3-mercaptopropyl (methyl) dimethoxysilane (MPMDS, 95% Aldrich) in the presence of Cetyltrimethylammonium bromide (CTAB, 98% APS) following the procedure described in the literature (Díaz et al., 2003). The molar composition of the mixture was as follows: (1 − x)TEOS: xMPMDS: 0.12CTAB: 0.27TMAOH: 18.8CH3OH: 77.7H2O. First, 2.2 g of CTAB was dissolved in 70.0 g of deionized water and 32.0 g of methanol, and then stirred for 30 min at room temperature. To this was added a mixture of 7.4 g of TEOS and 2.6 g of MPMDS dropwise, followed by 1.0 g of Tetramethylammonium hydroxide (TMAOH, 25 wt.% in water, Aldrich). The reaction was stirred at room temperature for 16 h to evaporate all the methanol. After that, hydrothermal treatment was applied at 95 °C for 48 h and the solid product obtained was separated by filtration and dried in air at 100 °C. The CTAB template was then removed by refluxing 1.5 g of solid with 205 mL ethanol/20 mL 37 wt.% HCl at 70 °C for 24 h. Finally, 1.0 g of the obtained SH-MCM-41 solid was oxidized by 20 mL of 30 wt.% H2O2 to obtain the SO3H-MCM-41 catalyst.

2.2

2.2 Characterization of the catalyst

Each catalyst was characterized by its physical and chemical properties. The textural properties of the catalysts in terms of the surface area and pore characteristics were quantified by N2 adsorption–desorption using an Autosorb-iQ instrument (Quantachrome, USA). The surface area was calculated from the isotherm data using the Brunauer-Emmett-Teller (BET) model, while the pore volume and pore diameter were calculated by Barrett–Joiner–Halender (BJH) model. The structural ordering was substantiated by Small-angle X-ray powder diffraction (SAXD) on a Rigaku TTRAX III X-ray diffraction spectrophotometer operating at a low angle using Cu Kα radiation in the 2θ angle range of 1–10° with a resolution of 0.02°. The presence of sulfhydryl and sulfonic groups on the MCM-41 surface was confirmed by Fourier transform infrared spectroscopy (FT-IR) using a Perkin Elmer Spectrum 100 FT-IR spectrometer. Thermal stability of catalyst was characterized by Perkin-Elmer TGA7 within the temperature range 100–800 °C at a heating rate of 10 °C/min. The amount of SO3H-groups on the MCM-41 surface was determined by back titration (Hofena et al., 2011).

2.3

2.3 2k factorial design

A 2k factorial design was used to screen the factors that significantly affect the efficiency of the fatty acid methyl ester (FAME) (biodiesel) production process. The catalyst loading (5 and 15 wt.%), reaction time (12 and 48 h), reaction temperature (100 and 140 °C) and molar composition of MPMDS (0.29 and 0.45) were defined as factors A, B, C and D, respectively. The calculation was performed by using MS-Excel. From the 24 factorial design, 16 combinations were performed (Table 1) with the percentage FAME yield as the response in each case.

Table 1 The experimental conditions for the factorsa for the 24 factorial design and the observed % FAME yield obtained.
Run no. A (wt.%) B (h) C (°C) D % FAME yield
1 5 12 100 0.29 8.2
2 15 12 100 0.29 16.8
3 5 48 100 0.29 22.8
4 15 48 100 0.29 63.7
5 5 12 140 0.29 16.1
6 15 12 140 0.29 19.9
7 5 48 140 0.29 16.6
8 15 48 140 0.29 82.5
9 5 12 100 0.45 9.4
10 15 12 100 0.45 19.7
11 5 48 100 0.45 20.9
12 15 48 100 0.45 66.2
13 5 12 140 0.45 17.3
14 15 12 140 0.45 25.7
15 5 48 140 0.45 18.6
16 15 48 140 0.45 79.9
Factors are coded as follows: A = catalyst loading (wt.%), B = reaction time (h), C = reaction temperature (°C), and D = molar composition of MPMDS.

2.4

2.4 Optimization by the Box–Behnken design

After the significant factors were verified (Section 2.3), optimization for FAME production was studied by response surface methodology using the Box–Behnken design to maximize the FAME yield. The quadratic regression model from the Box–Behnken design was used to predict the optimum condition, as shown in Eq. (1);

(1)
Y = β 0 + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 11 X 1 2 + β 22 X 2 2 + β 33 X 3 2 + β 12 X 1 X 2 + β 13 X 1 X 3 + β 23 X 2 X 3 , where Y is the percentage FAME yield (content), β0 is a constant, β1, β2 and β3 are linear coefficients, β11, β22 and β22 are quadratic coefficients, β12, β13 and β23 are interactive coefficients, and X1, X2 and X3 are the coded factors.

2.5

2.5 Transesterification reaction of RSO with methanol

Biodiesel was produced by transesterification of RSO at a 16:1 M ratio of methanol: oil, as previously reported (Samart et al., 2009). The mixture 5.0 g of RSO, 3.0 g of methanol and catalyst (wt.% of oil) were placed inside a 100 mL round-bottom flask equipped with a condenser while the cooling water was set at 10–15 °C using a thermostatic bath (Oliveira et al., 2010; Yin et al., 2012). The reactions were performed at stirring condition of 750 rpm, time and temperature condition were set up. At the end of the reaction time, the reaction was terminated by quenching in an ice-water bath. The excess methanol and catalyst were separated by evaporation and filtration, respectively. The FAME content was analyzed by gas chromatography (GC) Shimadzu GC-17A using DB-WAX (30 m length, 0.25 mm internal diameter and 0.25 μm film thickness) following the standard method of EN 14103. The FAME yield (% content) was calculated by Eq. (2);

(2)
% FAME = ( A ) - A EI A EI × C EI × V EI m × 100 % , where ΣA is the total peak area of the methyl ester peak from C14:1 to C24:1, AEI is the peak area of the internal standard (methyl heptadecanoate), CEI is the concentration of the internal standard (mg/mL), VEI is the volume of the internal standard solution (mL), and m is the mass of the sample (mg).

2.6

2.6 Catalyst reusability

The spent catalyst was separated from the reaction mixture by filtration and washing by methanol followed by n-hexane. The catalyst was then dried at 100 °C and reused at the optimal conditions.

3

3 Results and discussion

3.1

3.1 Characterization of catalyst

The catalyst was measured the textural properties by N2 adsorption desorption. All samples were degassed at 150 °C for 8 h under flow nitrogen prior to measurement. The analysis was carried with 40 sorption pressures which could enough to provide all information of mesoporous characteristics. The BET surface areas and pore characteristics were quantified and the results are summarized in Table 3. The surface area and pore diameters were slightly decreased 1.3- and 1.14-fold, respectively at the higher MPMDS molar ratio because the excess MPMDS hindered the formation of the mesoporous structures. Moreover, the pore volume was decreased (3.2-fold) due to pore filling by the propyl sulfonic acid groups. The N2 adsorption–desorption isotherms (Fig. 1A) indicated a IUPAC type IV isotherm, which corresponds to the mesoporous structure. The BJH pore size distribution (Fig. 1B) of both samples was uniformed. Moreover, pore diameter was decreased when the molar composition of MPMDS increased. The acid capacity of the catalyst was slightly (1.02-fold) enhanced by increasing the molar composition of MPMDS because the acid site depended on the amount of sulfonic groups (Table 3).

Table 2 The experimental conditions (factors)a and their code values (in parentheses) from the Box–Behnken design and the observed FAME yield (% content).
Run no. X1 (wt.%) X2 (h) X3 (°C) % FAME yield
Observed Predicted
1 5 (−1) 12 (−1) 120 (0) 8.40 8.0
2 15 (1) 12 (−1) 120 (0) 21.8 16.9
3 5 (−1) 48 (1) 120 (0) 30.8 35.7
4 15 (1) 48 (1) 120 (0) 81.3 81.7
5 5 (−1) 30 (0) 100 (−1) 21.6 23.8
6 15 (1) 30 (0) 100 (−1) 40.6 47.4
7 5 (−1) 30 (0) 140 (1) 40.2 33.4
8 15 (1) 30 (0) 140 (1) 66.9 64.7
9 10 (0) 12 (−1) 100 (−1) 12.1 10.3
10 10 (0) 48 (1) 100 (−1) 63.3 56.2
11 10 (0) 12 (−1) 140 (1) 16.3 23.4
12 10 (0) 48 (1) 140 (1) 68.1 70.0
13 10 (0) 30 (0) 120 (0) 64.9 64.6
14 10 (0) 30 (0) 120 (0) 65.5 64.6
15 10 (0) 30 (0) 120 (0) 63.4 64.6
Factors are coded as X1 = catalysts loading (wt.%), X2 = reaction time (h) and X3 = reaction temperature (°C).
Table 3 Physical and chemical properties of sulfonic acid functionalized MCM-41catalysts.
Catalyst Molar composition TEOS: MPMDS BET surface area (m2/g) Pore volume (cm3/g) Pore diameter (nm) Acid capacity (mmol/g)
0.29-SO3H-MCM-41 0.71: 0.29 395 0.16 5.61 1.39
0.45-SO3H-MCM-41 0.55: 0.45 303 0.05 4.90 1.42
(A) N2 adsorption–desorption isotherms and, (B) BJH pore size distribution and (C) SAXD patterns of (a) 0.29-SO3H-MCM-41 and (b) 0.45-SO3H-MCM-41.
Figure 1 (A) N2 adsorption–desorption isotherms and, (B) BJH pore size distribution and (C) SAXD patterns of (a) 0.29-SO3H-MCM-41 and (b) 0.45-SO3H-MCM-41.

The ordered mesoporous structure of catalyst was confirmed by SAXD analysis, where three diffraction peaks at a 2θ of 2.2°, 4.4° and 5.1°, which were designated as the (1 0 0), (1 1 0) and (2 0 0) planes, respectively, were observed (Fig. 1C). This supports that the hexagonal structure of the SO3H-MCM-41 catalyst was successfully synthesized. However, the decreasing intensity of these three peaks indicated the presence of the sulfonic group, since the presence of the alkylsulfonic molecule hindered the highly ordered pore arrangement (Rác et al., 2006).

The functional groups on the catalyst surface were evaluated by FT-IR analysis, where wave numbers at 450 cm−1 (SiO4, tetrahedron vibration), 800 cm−1 (Si—O—Si, symmetric vibration), a large band between 1000 and 1260 cm−1 (Si—O—Si, asymmetric vibrations), and 3400 cm−1 (SiO—H) were observed (Fig. 2). The wave numbers 1458 and 2989 cm−1 were assigned to —CH vibrations. SH-MCM-41 (spectra a and b) presented an additional peak at wave number 2570 cm−1 that was assigned to the SH-group, supporting that mercaptopropyl groups were introduced to the surface of MCM-41 successfully. After SH-MCM-41 was oxidized by H2O2 to SO3H-MCM-41 (spectra c and d) a new peak at wave number 1350 cm−1 (—SO3 group) was evident while that at 2570 cm−1 (SH-group) was lost supporting the complete transformation of SH-MCM-41 to SO3H-MCM-41.

Infrared spectra of the different sulfonic acid-MCM-41 catalysts: (a) 0.29-SH-MCM-41, (b) 0.45-SH-MCM-41, (c) 0.29-SO3H-MCM-41, (d) 0.45-SO3H-MCM-41 and (e) spent 0.29-SO3H-MCM-41.
Figure 2 Infrared spectra of the different sulfonic acid-MCM-41 catalysts: (a) 0.29-SH-MCM-41, (b) 0.45-SH-MCM-41, (c) 0.29-SO3H-MCM-41, (d) 0.45-SO3H-MCM-41 and (e) spent 0.29-SO3H-MCM-41.

Thermogravimetric analyses carried out for thermal stability verification of catalyst. According to DTG profile, both samples show two weight loss profiles at 380 °C and 470 °C (Fig. 3), which was the decomposition of sulfonic functional group and main chain of hydrocarbon of Propyl (methyl) sulfonic acid on MCM-41 (Díaz et al., 2000; Díaz et al., 2004). From thermogravimetric result, the decomposition of sulfonic acid did not present in transesterification temperature.

TG-DTG profiles (a) 0.29-SO3H-MCM-41 and (b) 0.45-SO3H-MCM-41.
Figure 3 TG-DTG profiles (a) 0.29-SO3H-MCM-41 and (b) 0.45-SO3H-MCM-41.

3.2

3.2 2k factorial design analysis of biodiesel production

The results of the 24 factorial designs (16 combinations of catalyst loading, reaction time, reaction temperature and molar composition of MPMDS, with the FAME yield as the response; shown in Table 1) were used to calculate the estimated effects and plotted against the probability (pK) (Fig. 4). It was clear that all factors, except the molar composition of MPMDS (factor D), and their interactions had a significant effect on the percentage FAME content. The main effect of the catalyst loading (factor A) and reaction time (factor B) equally influenced the FAME yield because the acid catalysis in the transesterification presented a very low catalytic activity. Therefore, the reaction time and catalyst loading strongly affected the obtained FAME yield, as did their interaction (factor AB) since there are limitations on the catalyst loading where an excess catalyst loading induces phase separation and so reduces the catalytic activity. The significant factors were then expressed as a linear regression model, as shown in Eq. (3);

(3)
Y = 31.53 + 30.54 X 1 + 29.76 X 2 + 6.10 X 3 + 21.62 X 1 X 2 + 4.29 X 1 X 3 + 5.97 X 1 X 2 X 3 where Y is the predicted value of the FAME yield (% content) and X1, X2 and X3 are the coded values (between −1 and 1) of the catalyst loading (wt.%), reaction time (h) and reaction temperature (°C), respectively (Table 2).
Normal probability plot of the estimate effects for the 24 factorial designs. (A = catalyst loading (wt.%), B = reaction time (h) and C = reaction temperature (°C), and see Table 1). Plots that lie on the line are those for factor D (Molar composition of MPMDS) and its combinatorial interactions with A, B and C, plus interaction BC.
Figure 4 Normal probability plot of the estimate effects for the 24 factorial designs. (A = catalyst loading (wt.%), B = reaction time (h) and C = reaction temperature (°C), and see Table 1). Plots that lie on the line are those for factor D (Molar composition of MPMDS) and its combinatorial interactions with A, B and C, plus interaction BC.

The reliability of the linear regression model was tested by the normal probability plot of residuals, and found to reasonably well fit a linear (straight line) pattern (R2 = 0.9601). Thus, the residuals obtained from the regression model followed the normality assumption (Fig. 5).

Normal probability plot of the residuals from the linear regression model showing the best fit linear regression line and correlation coefficient.
Figure 5 Normal probability plot of the residuals from the linear regression model showing the best fit linear regression line and correlation coefficient.

3.3

3.3 Optimization of FAME (biodiesel) production using the Box–Behnken design

Table 2 shows the Box–Behnken design with 15 experiments and the experimentally obtained FAME yield. The quadratic regression model of Box–Behnken design was presented in Eq. (4),

(4)
Y = 64.6 + 13.7 X 1 + 23.1 X 2 + 6.7 X 3 - 13.3 X 1 2 - 15.7 X 2 2 - 9.0 X 3 2 + 9.3 X 1 X 2 + 1.9 X 1 X 3 + 0.2 X 2 X 3 Eq. (4) was then used to predict the FAME yield under each of the 15 reaction conditions (Table 2) and then the theoretically predicted and experimentally derived values were compared by regression analysis (parity plot). The quadratic regression model (Eq. (4)) obtained theoretical values that were found to fit well with the experimental results with a correlation coefficient value R2 of 0.969 (Fig. 6).
Parity plot of the predicted versus experimental FAME yields and the best fit linear regression line and correlation coefficient.
Figure 6 Parity plot of the predicted versus experimental FAME yields and the best fit linear regression line and correlation coefficient.

The theoretical FAME yields with different reaction parameters were then calculated from Eq. (4) and the results presented as response surface and contour plots (Fig. 7). The effect of the catalyst loading and reaction time on the FAME content at a constant reaction temperature of 120 °C revealed an increasing FAME yield was predicted as the catalyst loading and reaction times were increased (Fig. 7A and B), giving a maximum FAME yield (81.9%) at a catalyst loading and reaction time of 14 wt.% and 48 h, respectively. At a constant reaction time of 30 h, the FAME yield increased with increasing catalyst loading level or reaction temperature (Fig. 7C and D), while at a constant catalyst loading of 10 wt.% the FAME content increased with increasing reaction time and temperature (Fig. 7E and F), but never exceeded that at 120 °C for 48 h with a 14 wt.% catalyst loading.

(A, C, E) Response surface and (B, D, F) contour plots of the FAME yield (% content) at various (A, B) catalyst loadings (wt.%) and reaction times (h), (C, D) catalyst loadings (wt.%) and reaction temperatures (°C), and (E, F) reaction times (h) and reaction temperatures (°C).
Figure 7 (A, C, E) Response surface and (B, D, F) contour plots of the FAME yield (% content) at various (A, B) catalyst loadings (wt.%) and reaction times (h), (C, D) catalyst loadings (wt.%) and reaction temperatures (°C), and (E, F) reaction times (h) and reaction temperatures (°C).

The optimal conditions for obtaining the highest FAME yield were calculated by maximization of the quadratic regression model, and found to be a catalyst loading of 14.5 wt.%, and a reaction time and temperature of 48 h and 129.6 °C, giving a maximum FAME yield of 84.0%. This was experimentally supported, where three replicated experiments at these optimal conditions gave a FAME yield of 83.10 ± 0.39%.

3.4

3.4 Catalyst reusability

The spent catalyst after use under the optimal set of conditions (Section 3.3) was then washed with solvents (see Section 2.7) and then reused under the same optimal conditions. The FAME yield obtained with successive reuse of the catalyst is shown in Fig. 8, where the FAME yield obtained after two, three and four uses of the catalyst was 1.03-, 1.08- and 1.09-fold lower than that for the unused catalyst. Thus, the SO3H-MCM-41 catalyst has a relatively high stability and may potentially be reusable. The spent catalyst after four reuse was presented the weak C⚌O spectra at wave number 1738 cm−1 from carbonyl containing compounds (Fig. 2) which was attracted by sulfonic group to reduce the catalytic activity of spent catalyst (Rubio et al., 2010).

Catalytic activity (in terms of % FAME yield) of the fresh SO3H-MCM-41 catalyst (1st use) and that of the regenerated catalyst after two, three and four uses in the transesterification of a 1:16 M ratio RSO: methanol mixture at a catalyst loading of 14.5 wt.% and a reaction temperature and time of 129.6 °C and 48 h per cycle.
Figure 8 Catalytic activity (in terms of % FAME yield) of the fresh SO3H-MCM-41 catalyst (1st use) and that of the regenerated catalyst after two, three and four uses in the transesterification of a 1:16 M ratio RSO: methanol mixture at a catalyst loading of 14.5 wt.% and a reaction temperature and time of 129.6 °C and 48 h per cycle.

4

4 Conclusions

The SO3H-MCM-41 catalyst was prepared and applied in FAME-based biodiesel production from RSO and methanol (1:16 M ratio). The physicochemical properties of the catalysts included a mesoporous structure with a high surface area and pore volume. The presence of the sulfonic groups on the mesoporous silica surface was confirmed. The catalytic activity of the SO3H-MCM-41 catalyst on FAME (biodiesel) production from RSO and methanol was evaluated using a 2k factorial design, where the catalyst loading, reaction time and reaction temperature were all significant factors, but not the molar ratio of MPMDS. The theoretical optimal set of conditions for FAME production was a catalyst loading of 14.5 wt.% and a reaction time and temperature of 48 h and 129.6 °C, giving a predicted and experimentally obtained FAME yield of 84.0 and 83.10 ± 0.39%, respectively. The spent catalyst could be reused for at least four times with only a 7% reduction of catalytic activity under these optimal conditions.

Acknowledgements

This research was supported by The Thailand Research Fund (TRF), The Commission on Higher Education (CHE) and Thammasat University under contract MRG5480200. Moreover, authors acknowledge Central Scientific Instrument Center (CSIC) for supporting characterization of catalyst.

References

  1. , , , , . Study of catalytic behavior of KOH as homogeneous and heterogeneous catalyst for biodiesel production. J. Taiwan Inst. Chem. Eng.. 2012;43:89-94.
    [Google Scholar]
  2. , , , , . Production of biodiesel using high free fatty acid feedstocks. Renew. Sust. Energy Rev.. 2013;16:3275-3285.
    [Google Scholar]
  3. , , , , . Application of the factorial design of experiments to biodiesel production from lard. Fuel Process. Technol.. 2009;90:1447-1451.
    [Google Scholar]
  4. , , , . Synthesis of biodiesel from edible, non-edible and waste cooking oils via supercritical methyl acetate transesterification. Fuel. 2010;89:3675-3682.
    [Google Scholar]
  5. , , . Statistical optimization for biodiesel production from waste frying oil through two-step catalyzed process. Fuel Process. Technol.. 2011;90:112-118.
    [Google Scholar]
  6. , , . Modern heterogeneous catalysts for biodiesel production: a comprehensive review. Renew. Sust. Energy Rev.. 2011;15:4378-4399.
    [Google Scholar]
  7. , . Biodiesel production from vegetable oils via catalytic and non-catalytic supercritical methanol transesterification methods. Prog. Energy Combust.. 2005;31:466-487.
    [Google Scholar]
  8. , , , , , . Combined alkyl and sulfonic acid functionalization of MCM-41-type silica. J. Catal.. 2000;193:283-294.
    [Google Scholar]
  9. , , , , . Synthesis of MCM-41 materials functionalised with dialkylsilane groups and their catalytic activity in the esterification of glycerol with fatty acids. Appl. Catal. A Gen.. 2003;242:161-169.
    [Google Scholar]
  10. , , , , . Study by TG–MS of the oxidation of SH-MCM-41 to SO3H-MCM-41. Thermochim. Acta. 2004;413:201-207.
    [Google Scholar]
  11. , , , . Inorganic heterogeneous catalysts for biodiesel production from vegetable oils: review. Biomass Bioenerg.. 2011;35:3787-3809.
    [Google Scholar]
  12. , . Biodiesel processing and production. Fuel Process. Technol.. 2005;86:1097-1107.
    [Google Scholar]
  13. , , , , . Novel titration method for surface-functionalised silica. Appl. Surf. Sci.. 2011;257:2576-2580.
    [Google Scholar]
  14. , , , . Periodic mesoporous organosilica functionalized sulfonic acids as highly efficient and recyclable catalysts in biodiesel production. Cat. Sci. Tech.. 2012;2:828-834.
    [Google Scholar]
  15. , , , . Development of heterogeneous base catalysts for biodiesel production. Bioresource Technol.. 2008;99:3439-3443.
    [Google Scholar]
  16. , . Biodiesel and renewable diesel: a comparison. Prog. Energy Combust.. 2010;36:364-373.
    [Google Scholar]
  17. , , , , , . A new heterogeneous acid catalyst for esterification: optimization using response surface methodology. Energy Convers. Manage.. 2013;65:392-396.
    [Google Scholar]
  18. , , , , , . Non-catalytic biodiesel process with adsorption-based refining. Fuel. 2011;90:1188-1196.
    [Google Scholar]
  19. , , , , , , , . Esterification of oleic acid with ethanol by 12-tungstophosphoric acid supported on zirconia. Appl. Catal. A Gen.. 2010;372:153-161.
    [Google Scholar]
  20. , , , , , . Advances on the development of novel heterogeneous catalysts for transesterification of triglycerides in biodiesel. Fuel. 2010;89:3602-3606.
    [Google Scholar]
  21. , , , , , . A comparative study of solid sulfonic acid catalysts based on various ordered mesoporous silica materials. J. Mol. Catal. A. 2006;244:46-57.
    [Google Scholar]
  22. , , , . Biodiesel production from high FFA rubber seed oil. Fuel. 2005;84:335-340.
    [Google Scholar]
  23. , , , , , , . Deactivation of organosulfonic acid functionalized silica catalysts during biodiesel synthesis. Appl. Catal. B Environ.. 2010;95:279-287.
    [Google Scholar]
  24. , , , . Heterogeneous catalysis of transesterification of soybean oil using KI/mesoporous silica. Fuel Process. Technol.. 2009;90:922-925.
    [Google Scholar]
  25. , , , , , , . Synthesis of biodiesel via homogeneous Lewis acid catalyst. J. Mol. Catal. A. 2005;239:111-115.
    [Google Scholar]
  26. , , , , , , . Synthesis of biodiesel from cottonseed oil and methanol using a carbon-based solid acid catalyst. Fuel Process. Technol.. 2009;90:1002-1008.
    [Google Scholar]
  27. , , , , , , . Synthesis of biodiesel from waste vegetable oil with large amounts of free fatty acids using a carbon-based solid acid catalyst. Appl. Energy. 2010;87:2589-2596.
    [Google Scholar]
  28. , , . Silica-bonded N-propyl sulfamic acid used as a heterogeneous catalyst for transesterification of soybean oil with methanol. Bioresource Technol.. 2011;102:9818-9822.
    [Google Scholar]
  29. , , , , , , , . Biodiesel production from esterification of oleic acid over aminophosphonic acid resin D418. Fuel. 2012;102:499-505.
    [Google Scholar]
  30. , , , , . Biodiesel production from vegetable oil using heterogenous acid and alkali catalyst. Fuel. 2010;89:2939-2944.
    [Google Scholar]
Show Sections