Optimization of Catalytic Glycerol Etherification with Ethanol in a

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Optimization of catalytic glycerol etherification with ethanol in a continuous reactor Caroline Ortega Terra Lemos, Leticia L. Rade, Marcos A.S. Barrozo, Lindoval Domiciano Fernandes, Lucio Cardozo-Filho, and Carla E. Hori Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b00194 • Publication Date (Web): 29 Mar 2017 Downloaded from http://pubs.acs.org on April 3, 2017

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Energy & Fuels

Optimization of catalytic glycerol etherification with ethanol in a continuous reactor Caroline O. T. Lemosa, Leticia L. Radea, Marcos A. de S. Barrozoa, Lindoval D. Fernandesb, Lucio Cardozo-Filhoc,d, Carla E. Horia,*

a

Faculdade de Engenharia Química, Universidade Federal de Uberlândia, Av. João Naves de Ávila 2121, Campus Santa Monica - Bloco 1K, 38400-902, Uberlândia, MG, Brazil.

b

Departamento de Engenharia Química, Universidade Federal Rural do Rio de Janeiro. Rodovia BR 465, Km 07, s/n - Zona Rural, 23890-000, Seropédica, RJ, Brazil.

b

Departamento de Agronomia e Departamento de Engenharia Química, Universidade Estadual

de Maringa, Av. Colombo 5790 – Bloco D90 Jardim Universitário, 87020-900, Maringa, PR, Brazil. d

Centro Universitário da Fundação de Ensino Octávio Bastos, Av. Dr. Octávio Bastos, 2439 - Jd Nova São João, São João da Boa Vista, SP, Brazil.

* Corresponding author. Email address: [email protected]

KEYWORDS: Glycerol, catalytic etherification, continuous reactor.

ACS Paragon Plus Environment

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ABSTRACT: In the last decades, biodiesel has emerged as a promising renewable energy source. However, its production usually leads to the formation of large amounts of glycerol as byproduct. This paper evaluates the catalytic glycerol etherification with ethanol over a series of catalyst in continuous reactor. Amberlyst 15 presented the best performance in terms of glycerol conversion and yield of ethers. This result was attributed to its high pore size and acidity. Beta zeolite (Si/Al 12.5) and niobic acid, both with lower acid strength and pore size, were almost inactive to convert glycerol into ethers. A central composite design was developed to optimize the performance of Amberlyst 15. An increase in catalyst amount enhanced both glycerol conversion and yield of ethers. However, high temperatures and low molar ratio favored side reactions. The optimized value for glycerol conversion was 91% and for yield of ethers was 13%, at different reaction conditions.


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1. INTRODUCTION

In order to face the energy needs of this century, society demands the development of clean and renewable sources to replace fossil fuels.1,2 Biodiesel emerged as a promising renewable energy source 3,4. However, its main production route (transesterification of vegetable oils) leads to the formation of large amounts of glycerol as byproduct.5 Despite already being employed in food and beverage, pharmaceutical, cosmetics and paper industries, the production of glycerol is still much higher than its demand. Additionally, glycerol cannot be used directly as an additive in fuels due to its high polarity, hygroscopicity and decomposition in acrolein.6 Therefore, there is an urgent need to find new applications for the surplus glycerol. The catalytic glycerol processing may occur by hydrogenolysis, polymerization, etherification, oxidation, dehydration, acetylation and transesterification. The etherification reaction is the most promising because it generates oxygenated compounds which may be directly added to fuels.7,8 The most common glycerol etherification method is the reaction with alkenes catalyzed by acids. However, according to Ferreira et al.9 the glycerol etherification with primary and secondary alcohols is the most important route in terms of fuel industrial application.5,7,10,11 Klepacova et al.12 studied the etherification of glycerol with tert-butyl alcohol catalyzed by resins of Amberlyst type and by H-Y and H-Beta zeolites in a batch reactor. Amberlyst is very active reaching 100% of glycerol conversion with selectivity to di- and tri-ethers above 92%. Cannilla et al.13 also investigated the etherification of glycerol with butanol in a batch reactor with a tubular water perm selective membrane using Amberlyst 15 as solid acid catalyst. According to the authors, relevant glycerol conversion was reached at temperatures higher than 140 °C. However, at such temperatures, the removal of water through the membrane favored


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glycerol dehydration. Ozbay et al. 14, 15 investigated the etherification of glycerol with tert-Butyl alcohol in batch and continuous flow reactors. Both studies showed the advantages of operating in a continuous mode, as this type of operation provides better contact between the catalyst and the reaction mixture and constant water removal. Pariente et al.7 analyzed the performance of different types of heterogeneous acid catalysts, including sulfonic resins, zeolites and graphited silicas in the glycerol etherification with ethanol. The best results were achieved using sulfonic-acid polystyrene resins of the Amberlyst family and zeolites with Si/Al ratios around 25. Yuan et al.5 studied the glycerol etherification with ethanol over a series of catalyst such as H-ZSM5, H-β and tungstophosphoric acid (HPW). HPW showed the highest conversion of glycerol (97%) at 160 °C, ethanol/glycerol of 6:1. Until now, the glycerol etherification reaction with ethanol was only carried out in batch type reactors. This feature decreases the conversion of glycerol into ethers due to the high water content in the reaction mixture at the end of the reaction. The presence of water may facilitate the reversible reaction of the ethers hydrolysis.5 Moreover, in batch reactors the energy costs are high and catalyst must be removed from the product, among other problems. Considering the relevance of the glycerol etherification route, the aim of this work is to study glycerol etherification with ethanol in a continuous reactor over three catalysts: commercial strong acid ion-exchange resins (Amberlyst 15), beta zeolite and niobic acid (HY-340). A lightoff curve was used to select the catalyst that showed the best performance of glycerol conversion/yield to ethers in a temperature range of 150-300°C. For this catalyst, a design of experiments (DOE) was performed to evaluate the effect of temperature, catalyst amount and ethanol:glycerol molar ratio as well as their interactions in the glycerol conversion and yield to ethers. Finally, a canonical analysis was applied in order to optimize the response variables.


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2. EXPERIMENTAL SECTION

2.1.

Materials

Glycerol and ethanol (purity 99.5%) supplied by Synth were used as reactants. Analytical standards for GC analysis were supplied by Sigma-Aldrich. The macroreticular sulfonic resins Amberlyst A15 provided by Dow Chemical Company was received in dry form and dried at 110 °C for 1 hour. The niobic acid (HY-340) was supplied by Companhia Brasileira de Metalurgia e Mineração (CBMM) in powder form and calcined in air flow at 300 °C for 2 hours to remove adsorbed impurities and water. The beta zeolite sample Si/Al of 12.5 was prepared according to methodology described in the U.S. patent.16 In this synthesis, a gel was prepared with the following molar composition: 25 SiO2: 1.0 Al2O3: 1.5 Na2O: 4.5 TEAOH: 240 H2O. To this end, 18.32 g of sodium aluminate were added in a mixture containing 148.78 g of 40% TEAOH and 95.66 g of deionized water. After stirring for 10 minutes, 337.23 g of colloidal silica (Ludox HS40, Sigma-Aldrich) were added and resulting suspension was stirred for 30 minutes and then heated at 150 °C for 10 days. The solid formed was recovered by filtration, dried at 100 °C for one night and calcined at 540 °C for 8 hours. For calcination it was used a heating rate of 0.2 °C/min, with two levels of 30 minutes each at 150 °C and 350 °C. Finally, the ion exchange was carried out using NH4Cl followed by calcination at 550 °C for 8 hours.

2.2.

Catalyst Characterization

Powder X-ray diffraction (XRD) of the samples was recorded on a Rigaku Miniflex II powder X-ray diffratometer using nickel filtered CuKα radiation (λ = 1.540 Å). The measurements for


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beta zeolite were obtained in the 2θ range of 2 to 50° (steps of 0.05°) with an account time of 3 seconds. XRD data for niobic acid were recorded in a 2θ range from 20 to 80° at a scan rate of 0.05°/step and scan time of 2 s/step. The total acidity of the materials was measured by temperature programmed desorption of NH3 (TPD-NH3), in a Quantachrome Chembet-3000 equipment. Firstly, the samples were treated at 300 °C under N2 flow rate of 20 mL/min by 1 h. The adsorption of NH3 was carried out at 100 °C for 30 minutes. Physisorbed NH3 was purged during 2 h under N2 flow rate of 20 mL/min. The heating rate was then adjusted to 10 °C/min, from 100 °C to 700 °C, to perform the desorption of chemisorbed NH3. Textural analysis of the catalysts was carried out using N2 gas adsorption–desorption isotherms at -196.15 °C using Quantachrome Nova 1200 equipment. Surface area measurements were made according to the BET method and the pore size distribution was calculated using the tmethod (micropores) and BJH method (mesopores) with data determined from the desorption branch of the isotherms. The validity of the method was based on the BET constant C associated to the interaction of adsorbate/adsorbent, and c>0 was employed as isotherms adjustment region.

2.3.

Reaction Procedure

Etherification reactions were carried out in a fixed bed using a tubular reactor made of stainless steel tubing (316 L 3/8 in OD, inner diameter 6.8 mm, 30 cm). The feeding of substrate in the system was controlled by a high pressure liquid pump (LabAlliance, Series III) which was adjusted to a flow rate of 0.40 mL/min. The residence time was calculated as the time that the substrate remains in contact with the catalyst, which ranged from 12 to 80 seconds for 0.12 and 0.80 g of catalyst respectively. After filling the system with the substrate, the process of heating


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the furnaces started. The temperature was monitored by thermocouples connected to the reactors, with a precision of 2 °C. Finally, when the temperatures were stabilized at the desired conditions and after waiting twice the time necessary to fill all the reactor system, samples were collected. The etherification of glycerol with ethanol yields the following desired products: monoethylglycerols (MEG), di-ethylglycerols (DEG) and tri-ethylglycerols (TEG). Reaction products and remaining glycerol were diluted with ethanol and analyzed by gas chromatography (Shimadzu-2014) using a CP-WAX 52 CB column (30 m x 0.25 mm x 0.25 µm) and a flame ionization detector (FID) according to the methodology of Melero et al.11 The retention times were 6.9, 5.9, 6.1, 9.6 minutes for MEG, DEG, TEG and glycerol, respectively. The injection and detector temperatures were 250 °C. Analyses were carried out in split mode of 1:100 with temperature program from 50 to 210 °C (with a heating step of 70 °C/min) and at 210 °C for 10 minutes isothermally. The 1,4-butanediol analytical standard was used after a calibration with commercial MEG and glycerol. In the case of DEG and TEG, non-commercially available, response factors were extrapolated from that of MEG assuming similar behavior. Glycerol conversion (X), selectivity of MEG/DEG/TEG (S) and yield of MEG/DEG/TEG (Y) were calculated using the following equations:

=

⁄ ⁄

× 100

(1)

=

⁄ ⁄

× 100

(2)

=

⁄ × ⁄

100

(3)


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All the solid materials were tested in a temperature range of 150 to 300 °C, molar ratio ethanol/glycerol of 10/1 and 0.4 g of catalyst in order to evaluate the best catalyst to convert glycerol into ethers. The catalyst which presented the best performance was then chosen to have its performance optimized using a design of experiments methodology.

2.4.

Statistical analysis using design of experiments

The design of experiments (DOE) was used for quantifying the effects of the most significant variables, as well as their interactions on the glycerol conversion and yield of ethers. A Central Composite Design (CCD) with response surface method was used to determine the optimal reactions conditions. Three independent variables were selected:

temperature (XT),

ethanol/glycerol molar ratio (XM.R.) and catalyst amount (XC.A.). Each variable was investigated at five levels: -α, -1, 0, +1 and +α (coded levels), as shown in Table 1, where α is the axial point of 1.414 (orthogonal design). The selection of the levels was based on results obtained in preliminary tests. According to the experimental results for glycerol conversion and yield of ethers, a regression or statistical model was fitted. The significant terms in the model were found by analysis of variance (ANOVA) for each response. The statistically non-significant terms (p > 0.10) were removed from the initial models by stepwise selection and the experimental data were refitted to produce the final model. The central point experiment was repeated four times in order to determine the variability of the results and assess the experimental error. In all experiments performed, the feeding of substrate in the system was adjusted to a flow rate of 0.40 mL/min.

2.5.

Optimization using canonical analysis


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Canonical correlation analysis was used to study the interrelationships among sets of multiple dependent and independent variables for glycerol conversion and yield of ethers. An empirical equation was fitted to the experimental data which correlates the predict response with independent variables and first order parameters vectors and a matrix of the quadratic parameters. The maximum value for the response will be a set of conditions such that the derivatives are simultaneously zero. This point is called as stationary point of the fitted surface and can be a maximum, minimum or a saddle point, depending of the arrows sign (!i). Thus, the response function can be expressed in terms of new variables whose axes correspond to the principal axes of the contour system. The form of the function in terms of these variables is called canonical form and is given by Equation 4. The software Maple 17 was used to perform this analysis.

" = "# + !% &% ' + !' &' ' + … + !) &) '

(4)

3. RESULTS AND DISCUSSION

3.1.

Characterization of catalysts

XRD patterns of beta zeolite exhibited only the typical features, showing the characteristic diffraction peaks of beta zeolite, at 2θ = 7.5 – 8° and 22.4°, thus indicating high crystallinity without impurities.17 XRD patterns of niobic acid calcined at 300 °C showed an amorphous structure and this result is in agreement with the data reported by Lebarbier et al.18 Table 2 summarizes the most relevant physicochemical properties for the Amberlyst 15, beta zeolite and niobic acid. The acidity of the three samples was evaluated by NH3 adsorption and


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the results are presented in Table 2. The acidity of Amberlyst 15 was significantly higher than the other samples, followed by beta zeolite and niobic acid. Catalysts showed different surface areas, ranging from 53 to 434 m2/g and porosities between 0.0042 and 0.40 cm3/g. Amberlyst 15 presented a mesopore volume and mesopore size much higher than the other catalysts studied. Beta zeolite and niobic acid showed to be structured both by micro and mesopores. The presence of mesopores should favor the access to the active sites.

3.2.

Light off results

The light off curves for each type of catalyst are presented in Figure 1. The catalysts studied were active in different temperature ranges. The highest glycerol conversion value (85 %) was reached using Amberlyst 15 as solid acid at 200 °C. However, it should be noted that even with a low conversion of 53 % at 175 °C the ether yield was higher than the yield obtained at higher temperature. This behavior was repeated for the other catalysts studied, since the increase in the reaction temperature favors the formation of undesirable compounds such as acrolein and diethyl ether. Moreover, at high temperatures, water forms at a higher rate, favoring the inverse reaction and competing for the acid sites. In the presence of water, thermodynamic constraints and problems related to the stability of the catalyst may inhibit the reaction12,

19, 20

. Beta zeolite

reached a maximum conversion of 13 % at 300 °C. For this catalyst, glycerol conversion increases linearly with increasing temperature, however the ether yield remained very low over the range evaluated. One possible reason for this small conversion is the lower acidity presented by this sample compared to Amberlyst 15. Another explanation for this low efficiency observed for Beta zeolite is its small pore size (micropores around 6 Å). The average molecule size of glycerol é 4.3 Å and its smallest projection is around 4 Å. The addition of ethoxy groups to


10

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glycerol molecule will increase the molecule size (see molecules below). For MEG, the smallest projection would be around 5 Å and the diffusion would still be viable. For DEG and TEG, the diffusion limitations would be very severe, as previously reported by Yuan et al.5 and Klepacova et al.12. On the other hand, Amberlyst 15 is characterized by an average pore diameter much larger than beta zeolite. The niobic acid was quite inactive in the glycerol conversion and this fact may be related to its low acidity when compared to the other tested catalysts. Suitable textural properties of an open porous accessible structure and the high acidity characteristic of Amberlyst 15 lead to a best catalytic activity and production of desired products. Thereby, this catalyst was chosen to be used in the next steps of the study.

3.3.

Development of regression model and response surface

The experimental results obtained at different operating conditions used in the glycerol etherification with ethanol are presented in Table 3. As it can be seen, the glycerol conversion at different reaction conditions showed a large sensitivity to the variables studied (ranging from 0 to 91%). The highest yield of ethers (9%) was obtained by entry 7 at 167 °C, 14:1 ethanol:glycerol molar ratio and 0.68 g of catalyst. The temperature influences the distribution of the desired products. A higher temperature accelerates glycerol conversion and enhances the selectivity toward products DEG and TEG, whereas the selectivity to MEG decreased, as it can be seeing comparing entries 1 and 2, 3 and 4, 5 and 6 and 7 and 8. The influence of ethanol/glycerol molar ratio on the products selectivity cannot be easily evaluated. However the yield of ethers enhances with the increase of the molar ratio, according to entries 1 and 3, 5 and 7 and, 6 and 8. The glycerol conversion and yield of ethers are good


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results considering that the residence time (from 12 until 80 seconds) is much lower than the literature data presented until now.5, 7, 11 The arithmetical averages and the standard deviations were calculated for the central point experiments: glycerol conversion of 61% ± 1% and yield of ethers of 4% ± 1%. The results obtained were then analyzed using analysis of variance (ANOVA) and is the results are shown in Table 4. The ANOVA summary showed that the models obtained for conversion and yield of ethers had both a good correlation with the response variable. For glycerol conversion the quadratic term of ethanol/glycerol molar ratio and the three interaction between variables terms were not significant at a confidence interval of 90%. On the other hand, for yield of ethers only the interaction temperature/molar ratio and the quadratic term of catalyst amount were not significant (p-value higher than 0.1). From the matrix generated by the experimental data (Table 3) and after eliminating the insignificant parameters for CCD, a multiple regression was developed for each response variable. The empirical equations obtained, expressed in coded factors, is given by Equations 5 and 6.

= 59 + 15.98. + 12.7112 + 26.2145 − 7.50. ' − 745' (r2=0.92)

(5)

= 3.67 − 0.42. + 1.1012 + 2.4145 − 0.38.45 + 0.881245 − 0.71. ' + 0.5412 ' (r2=0.98)

(6)

Figures 2 and 3 show the response surfaces for glycerol conversion and ethers yield predicted by the statistical models presented on Equations 5 and 6. Statistical analysis of the studied


12

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experimental range identifies the catalyst amount (CA) as the most important factor in the glycerol conversion response (Eq. 5). A higher amount of catalyst leads to a consequently longer residence time and, in this way, the glycerol conversion will be beneficiated. The second most important factor is the temperature (T) followed by the ethanol/glycerol molar ratio (MR). That means that an increase in any of these variables produces an increase in the conversion of glycerol. However the enhancement of this response with temperature is more significant at high values of the molar ratio and the corresponding improvement with the molar ratio is also more substantial at high temperatures. Nevertheless, under high temperatures, a lot of non-desired compounds are produced by side reactions. Equation 5 shows two quadratic terms which indicates a non-linear behavior of the system: at higher catalyst amount and temperature, these parameters will start to have a negative effect on the glycerol conversion due to its degradation process and problems related to mass transfer. In terms of ethers yield, it is observed from Equation 6 that this response is affected by the linear terms of all studied parameters. Molar ratio and catalyst amount have positive effects on ethers yield, but temperature has a negative effect. The glycerol etherification is enhanced when the amount of ethanol present in the reaction medium is increased. In addition, the quadratic effects of temperature and molar ratio have a significant influence on the ethers yield, which indicates that the increase or decrease in these variables do not produce a constant variation on response due to curvature effects.

3.4.

Optimization

Aiming to have a larger set of data close to the region of the highest values of the responses (glycerol conversion and yield of ethers), additional experiments were performed in this region.


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Table 5 shows the results of these new experiments. The experimental values and coded reaction parameters of Table 5 were coupled to the values of central composite design and a new multiple regression was fitted for each response variable. Thus, the canonical analysis for the new fitted models was applied and the stationary points have been found. Canonical forms of these new models are presented in Equations 7 and 8. It can be seen that the stationary points are maximum points for both response variables (negative values for the eigenvalues).

" 9 = −28.38&% − 22.42&' − 11&: + 93.44

(7)

"9 = −6.78&% − 1.42 − 0.88&: + 12.77

(8)

The maximum predicted glycerol conversion was 93% at 193 °C, glycerol/ethanol molar ratio of 10.98/1 and 0.61 g of catalyst. The experimental value of glycerol conversion at this reaction condition was 91%. For yield of ethers the maximum predicted value was 13% at 170 °C, molar ratio of 17.34/1 and 0.57 g of Amberlyst 15. The experimental result obtained at this operating conditions was also 13%. Values of ethers yield are not usually presented in previous studies. However, Melero et al.11 presented the ethers yield as optimized response variable and the maximum value obtained was 40% using ethanol and modified-SBA-15 with arenesulfonic as catalyst, after 4 hours of batch reaction. Therefore, maximum values of the response variables optimized in this work are good results since the residence time is much smaller than the residence time presented on the current literature data. Furthermore, the use of continuous mode reactors proposed in this study favors the intensification and scalability of the process.


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4. CONCLUSIONS

Amberlyst 15 showed better performance in terms of glycerol conversion and yield of ethers than beta zeolite and niobic acid. According to the central composite design, the conversion of glycerol was influenced positively by catalyst amount followed by temperature and molar ratio. For yield of ethers, the catalyst amount was the most important positive factor followed by molar ratio, however, temperature had a negative effect. The canonical analysis led to a maximum value of glycerol conversion of 91% and a maximum yield of ethers of 13%, even with a residence time around 60 seconds in both cases.

AUTHOR INFORMATION *Carla Eponina Hori Faculdade de Engenharia Química, Universidade Federal de Uberlândia, Av. João Naves de Ávila 2121, Campus Santa Monica - Bloco 1K, 38400-902, Uberlândia, MG, Brazil. Email address: [email protected]

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. All the authors contributed equally.


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ACKNOWLEDGMENT

The authors wish to acknowledge the financial support of CAPES, CNPq, Vale S.A. and FAPEMIG and CBMM for providing the niobic acid sample (HY-340).

ABBREVIATIONS

HPW, tungstophosphoric acid; DOE, design of experiments; GC, gas chromatography; CBMM, Companhia Brasileira de Metalurgia e Mineração; XRD, powder X-ray diffraction; TPD-NH3, temperature programmed desorption of NH3; MEG, mono-ethylglycerols; DEG, diethylglycerols; TEG, tri-ethylglycerols; FID, flame ionization detector; CCD, central composite design; ANOVA, analysis of variance; CA, catalyst amount; T, temperature; MR, molar ratio.

REFERENCES

(1) Galan, M. I., Bonet, J., Sire, R., Reneaume, J. M., Ples, A. E. Bioresour. Technol. 2009, 100, 3775–3778. (2) Sivaiah, M. V., Robles-Manuel, S., Valange, S., Barrault, J. Catal. Today 2012, 198, 305– 313. (3) Izquierdo, J. F., Montiel, M., Pale, I., Outo, P. R., Gala, M., Jutglar, L., Villarrubia, M., Izquierdo, M., Hermo, M. P., Ariza, X. Renew. Sust. Energ. Rev. 2012, 16, 6717–6724. (4) Di Serio, M., Casale, L., Tesser, R., Santacesaria, E. Energy Fuels 2010, 24, 4668-4672.


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(5) Yuan, Z., Xia, S., Chen, P., Hou, Z., Zheng, X. Energy Fuels 2011, 25, 3186-3191. (6) Srinivas, M., Raveendra, G., Parameswaram, G., Sai Prasad, P. S., Lingaiah, N. J. Mol. Catal. A. Chem. 2016, 413, 7–14. (7) Pariente, S., Tanchoux, N., Fajula, F. Green Chem. 2009, 11, 1256-1261. (8) Gholami, Z., Abdullah, A. Z., Lee, K. T. Appl. Catal., A: Gen. 2014, 479, 76–86. (9) Ferreira, M. O., Cardozo-Filho, L., Silva, C., Sousa,E. M. B. D. Lat. Am. Appl. Res. 2014, 44, 47-56. (10) Frusteri, F., Arena, F., Bonura, G., Cannila, C., Spadaro, L., Di Blasi, O. Appl. Catal., A: Gen. 2009, 367, 77–83. (11) Melero, J. A., Vicente, G., Paniagua, M., Morales, G., Munoz, P. Bioresour. Technol. 2012, 103, 142-151. (12) Klepacova, K., Mravec, D., Bajus, M. Appl. Catal., A: Gen. 2005, 294, 141–147. (13) Cannilla, C., Bonura, G., Frusteri, L., Frusteri, F. Chem. Eng. J. 2015, 282, 187–193. (14) Ozbay, N., Oktar, N., Dogu, G., Dogu, T. Ind. Eng. Chem. Res. 2012, 51, 8788–8795. (15) Ozbay, N., Oktar, N., Dogu, G., Dogu, T. Top. Catal. 2013, 56, 1790-1803. (16) Wadlinger, R.L., Kerr, G.T., Rosinski, E.J. U.S. patent 3,308,069, March 1967. (17) Gonzalez, M. D., Salagre, P., Linares, M., Garcia, R., Serrano, D., Cesteros, Y. Appl. Catal., A: Gen. 2014, 473, 75–82. (18) Lebarbier, V., Houalla, M., Omfroy, T. Catal. Today 2012, 192, 123-129.


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Page 18 of 24

(19) Ayoub, M., Khayoon, M.S., Abdullah, A.Z. Bioresour. Technol. 2012, 112, 308–312. (20) Cannilla, C., Bonura, G., Frusteri, L., Frusteri, F. Environ. Sci. Technol. 2014, 48, 60196026.


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Page 19 of 24

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Energy & Fuels

TABLES AND FIGURES

Table 1. Central composite design with the three independent variables evaluated. Levels -α

-1

0

+1

+α

(XT) Temperature (°C)

160

167

185

203

210

(XM.R.) Molar ratio

4:1

6:1

10:1

14:1

16:1

(XC.A.) Catalyst amount (g)

0

0.12

0.40

0.68

0.80

Table 2. Physicochemical properties for the solid materials. Catalyst

Acidity (mmol/g)

Surface (m2/g)

area Pore (cm3/g)

volume Pore size (Å)

Meso

Micro

Meso

Micro

Amberlyst 15

4.70

53*

0.40*

-

300*

-

Beta zeolite

0.29

434

0.05

0.15

15

6

Niobic acid

0.10

111

0.079

0.0042

30

9

*Provided by the supplier.

Table 3. Experimental conditions and results for glycerol etherification with ethanol over Amberlyst 15 obtained using central composite design.


19

Energy & Fuels

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

Entry

T (°C)

MR

CA (g)

X (%)

Page 20 of 24

Y (%)

S (%) MEG

DEG

TEG

1

167

6

0.12

5

1

95

3

2

2

203

6

0.12

25

1

94

6

0

3

167

14

0.12

12

2

97

2

1

4

203

14

0.12

45

1

88

9

3

5

167

6

0.68

26

5

95

3

2

6

203

6

0.68

83

3

92

6

2

7

167

14

0.68

87

9

87

8

5

8

203

14

0.68

91

7

83

10

7

9

160

10

0.40

12

2

92

7

1

10

210

10

0.40

67

2

92

7

1

11

185

4

0.40

36

3

94

4

2

12

185

16

0.40

76

6

90

6

4

13

185

10

0.00

0

0

0

0

0

14

185

10

0.80

81

7

86

9

5

15

185

10

0.40

60

4

93

5

2

16

185

10

0.40

61

3

91

6

3

17

185

10

0.40

62

4

91

6

3

18

185

10

0.40

59

4

91

6

3

Note: T, temperature; MR, ethanol/glycerol molar ratio; CA, catalyst amount; X, conversion of glycerol; Y, yield to ethers; S, selectivity of MEG, DEG and TEG.

Table 4. Analysis of variance (ANOVA) for response surface quadratic model for, A) glycerol conversion; and B) Yield of ethers. Source

Sum squares

of Degrees freedom

of Mean square

F-value

P-value


20

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Energy & Fuels

A Model

14524.55

9

1613.84

15.87

0.000000a

T

3064.95

1

3064.95

30.15

0.000580a

MR

1939.74

1

1939.74

19.08

0.002387a

CA

8245.13

1

8245.13

81.10

0.000018a

T2

449.85

1

449.85

4.42

0.068558a

MR2

4.52

1

4.52

0.04

0.838186b

CA2

391.86

1

391.86

3.85

0.085225a

T.MR

200.00

1

200.00

1.97

0.198331b

T.CA

8.00

1

8.00

0.08

0.786197b

MR.CA

220.50

1

220.50

2.17

0.179043b

Error

813.31

8

101.66

Model

100.02

9

11.11

37.03

0.000000a

T

2.08

1

2.08

6.93

0.029896a

MR

14.61

1

14.61

48.70

0.000115a

CA

69.60

1

69.60

232.00

0.000000a

T2

4.01

1

4.01

13.37

0.006411a

MR2

2.35

1

2.35

7.83

0.023255a

CA2

0.01

1

0.01

0.03

0.834784b

T.MR

0.12

1

0.12

0.40

0.536571b

T.CA

1.12

1.

1.12

3.73

0.088757a

MR.CA

6.12

1

6.12

20.40

0.001951a

Error

2.40

8

0.30

B

a

Significant at 90% confidence interval.

b

Not significant at 90% confidence interval.


21

Energy & Fuels

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Page 22 of 24

Table 5. Experimental glycerol conversion and yield of ethers of the reactions added to central composite design. Entry

T (°C)

MR

CA (g)

Experimental value S (%) (%) MEG

DEG

TEG

Glycerol conversion 19

213

7.94

0.83

77

92

7

1

20

211

9.82

0.87

89

82

12

6

21

209

11.69

0.90

91

89

7

4

22

205

15.44

0.98

88

86

10

4

23

184

19.44

0.64

65

88

8

4

24

190

15.71

0.61

82

87

8

5

25

167

7.08

1.58

5

96

2

2

26

163

13.91

1.87

9

95

3

2

27

161

17.32

2.01

12

90

6

4

28

159

20.73

2.15

8

94

3

3

Yield ethers

of

Note: T, temperature; MR, ethanol/glycerol molar ratio; CA, catalyst amount.

(a)

(b)


22

Page 23 of 24

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Energy & Fuels

Figure 1. Glycerol conversion (a) and yield of ethers (b) at different temperatures. Reactions conditions: Molar ratio ethanol/glycerol=10/1; Catalyst amount=0.40 g.


23

Energy & Fuels

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(a)

Page 24 of 24

(b)

Figure 2. (a) Response surface for glycerol conversion against ethanol/glycerol molar ratio and temperature; (b) Response surface for glycerol conversion against catalyst amount and ethanol/glycerol molar ratio.

(a)

(b)

Figure 3. (a) Response surface for yield of ethers against catalyst amount and temperature; (b) Response surface for yield of ethers against catalyst amount and ethanol/glycerol molar ratio.


24

Optimization of Catalytic Glycerol Etherification with Ethanol in a

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