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Development of kinetic model for hydrogenolysis of glycerol over Cu/MgO catalyst in a slurry reactor Nitin Naresh Pandhare, Satyanarayana Murty Pudi, Smita Mondal, Keval Pareta, Manish Kumar, and PRAKASH BISWAS Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.7b03684 • Publication Date (Web): 06 Dec 2017 Downloaded from http://pubs.acs.org on December 6, 2017

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Industrial & Engineering Chemistry Research

Development of kinetic model for hydrogenolysis of glycerol over Cu/MgO catalyst in a slurry reactor

Nitin Naresh Pandhare a, Satyanarayana Murty Pudi a, Smita Mondala, Keval Pareta a, Manish Kumar a and Prakash Biswas a*

a

Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee-

247667, Uttarakhand, India.

*Corresponding Author: Tel.: (+91)-1332-28-5820; Fax: (+1)-1332-27-6535 E-mail address: [email protected]; [email protected]

1 ACS Paragon Plus Environment

Industrial & Engineering Chemistry Research 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

Abstract Kinetics of the liquid phase hydrogenolysis of glycerol was investigated over 35 wt.% Cu/MgO catalyst in a slurry batch reactor. Power law and Langmuir-Hinshelwood-HougenWatson (LHHW) model was tried to fit the experimental data. To develop the kinetic model, a new reaction mechanism is proposed. To simulate the experimental concentration-time data, the set of differential equations were developed and solved numerically by using ode23 stiff system coupled with genetic algorithm optimization technique. Kinetic parameters were estimated by minimizing the residual sum of squares between the predicted and experimental concentrations of glycerol, 1,2-PDO and ethylene glycol (EG). Power law showed that hydrogenolysis of glycerol over 35 wt.% Cu/MgO catalyst followed the overall reaction order of 1.2 with respect to glycerol with an activation energy of 84.9 kJ/mol. The LHHW model satisfactorily correlated the rate data and this model showed good fit between the experimental and calculated concentration of glycerol as well as products. Keywords: Copper-magnesia catalyst, hydrogenolysis of glycerol, 1,2-propanediol, LHHW model.


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1. Introduction Recently, biodiesel has been emerged as a potential alternative transportation fuel produced from renewable sources such as vegetable oils and animal fats. The world’s biodiesel production is expected to reach 33 billion liters per year by 2020. Biodiesel is considered as an environment friendly transportation fuel as compared to the conventional diesel because of its high flash point, better viscosity, calorific value similar to fossil source derived diesel fuel and it can be blended in any proportion with conventional diesel.1 However, during the production of biodiesel, ~10 wt.% glycerol is produced as by-product and it is expected that glycerol production will exceed the demand in the near future.2 This crude glycerol could be used as a renewable feedstock for the production of various value added chemicals and fuels additives. In the current literature various catalytic value addition processes of glycerol such as hydrogenolysis, oxidation, etherification, reforming and carboxylation etc. have been proposed.3 Among all these conversion processes, selective conversion of glycerol to 1,2-propanediols (1,2PDO) has attracted significant interest due to the high market demand of 1,2-PDO. Hydrogenolysis reaction involves selective dissociation of C=O and C-C bond in glycerol with the simultaneous addition of hydrogen. For glycerol hydrogenolysis, 1,2-PDO, 1,3-propanediol (1,3-PDO), hydroxyl acetone (acetol) and ethylene glycol (EG) has been reported as primary reaction products. However, other degradation products such as methanol, ethanol, 1-propanol (1-PO), and 2-propanol (2-PO) are also reported. During past two decades, various noble and non-noble metal catalysts have been developed and evaluated for hydrogenolysis of glycerol in liquid as well as vapour phase. Noble metal catalysts such as Pt,4-7 Ru,6,8,9 Rh,5,6 Pd,5,6,10 Re,10 and Ag,11 have been reported as highly active. However, the primary drawback of noble metals are high cost and low selectivity to 1,23 ACS Paragon Plus Environment


PDO due to the over hydrogenolysis. Among the non-noble metals, Cu-based catalysts,12-18 supported on Al2O3,15,19 Cr2O3,12,20 MgO,21-23 SiO2,14,24,25 ZnO,16,26 and ZrO2,27 have been shown are very active and selective to 1,2-PDO due to the inherent ability of copper to cleave the C-O bond. Recently, we have shown ~100% conversion of glycerol with ~93% selectivity to 1,2-PDO over highly efficient Cu/MgO catalysts.28 The reaction kinetics for hydrogenolysis of glycerol is not well studied. Previous literature primary focused on the development of catalyst and catalytic process, the information regarding the reaction kinetics is only a few. The first kinetics study on hydrogenolysis of lower polyhydric alcohols was published.29 Langmuir-Hinshelwood type mechanism was developed in presence of a commercial 5 wt.% Ru/C catalyst. In their study, the importance of competitive adsorption between 1,2-PDO and EG was highlighted. The side reactions led to the formation of degradation products were not considered. Torres et al.30 studied the kinetics of liquid phase hydrogenolysis glycerol to 1,2-PDO by using a bimetallic Ru-Re/C catalyst. Reaction was conducted in batch mode in a multiple slurry reactor in the temperature and H2 pressure range of 220-240oC and 2.4-9.6 MPa, respectively. Power law type kinetics was considered for fitting the experimental data due to the complexity of the reaction scheme. Xi et al.31 proposed a kinetic model based on three step reaction mechanism i.e. dehydrogenation-dehydration-hydrogenation in a trickle bed reactor in presence of Co-Pd-Re/C catalyst. Reaction kinetic parameters were determined by using nonlinear regression analysis. Zhou et al.32 proposed a two site LangmuirHinshelwood model based on two step reaction mechanism i,e. dehydration-hydrogenation over Cu-ZnO-Al2O3 catalysts in a tubular fixed bed reactor. Few more study reported Power law type kinetics in presence of Pd-CuCr,33 Ag-OMS,34 Cu0.4/Zn0.6Mg5.6Al2O8.6,35 Cu/SiO2,36 and Cu:Zn:Cr:Zr,37 catalysts, respectively. Recently, an intrinsic glycerol hydrogenolysis kinetics are


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developed experimentally on a stable, commercial copper-based catalyst in an isothermal tricklebed reactor.38 A comprehensive kinetic model was developed by considering the elementary steps for hydrogenolysis of glycerol and the model was fitted the experimental data over a wide range of operating conditions. In this study, kinetics of the liquid phase hydrogenolysis of glycerol was investigated in presence of 35 wt.% Cu/MgO catalyst. The effect of temperature, pressure, and glycerol concentration on the catalytic activity and products selectivity were investigated. Results showed that the product selectivity was significantly affected by the reaction temperature, pressure and glycerol concentration, respectively. Power law and Langmuir-Hinshelwood-Hougen-Watson (LHHW) models were developed and the experimental data was tried to fit the kinetic models. In the model development, surface adsorption, surface reaction and surface desorption steps of the reactants as well as products molecules on the catalyst active sites were considered. The optimum values of the kinetic parameters were determined by minimizing the residual sum of squares between the experimental and model simulated glycerol concentration value for all the experiments. Results demonstrated that, LHHW model could satisfactorily correlated the experimental and the model simulated concentrations of product.

2. EXPERIMENTAL 2.1. Catalyst preparation 35 wt.% Cu/MgO catalyst was prepared by precipitation-deposition method.28 Initially, an aqueous solution of Cu(NO3).3H2O (> 99%, Himedia Chemicals, India) was precipitated by the drop-wise addition of an aqueous solution of 1 M NaHCO3 (> 99.8%, Thomas Baker, India) until the pH of the solution was 8-9. After precipitation, the calculated amount of MgO light



(98%, Thomas Baker, India) was added to the solution under continuous stirring for 6 h and the resulting solution was aged at ~25oC for 12 h. The slurry obtained was filtered, washed thoroughly with distilled water followed by drying for 12 h at 110oC. The dried solid was calcined at 550oC for 4 h in presence of air. 2.2. Activity test The catalytic activity was evaluated in a 250 ml high pressure autoclave (Amar Equipment, India) equipped with an temperature controller, a mechanical stirrer and sample collection port.28 The schematic of the reactor is shown in Figure 1. Prior to each experiment, the catalyst was reduced in a separate tubular reactor at 350oC for 3 h in presence of H2 (50 ml/min). In a typical run, 100 g of 20 wt.% aqueous glycerol solution was taken as feed and required amount of reduced catalyst was added into the reactor. After being sealed, the reactor was purged with pure hydrogen for 3-4 times to remove the air present inside the reactor. The reaction time was started to count after achieving the desired temperature of the reaction mixture. For the kinetic study, the experiments were conducted at different reaction temperature (190-230oC), pressure (3-6 MPa) and feed concentration (20-60 wt.%), respectively. For all the kinetic experiments, the catalyst loading was kept constant at 8 wt.% with respect to the wt.% of glycerol present in the reaction mixture. The detail of product analysis, initial catalyst screening, fresh and used catalyst characterization, effect of catalyst loading, product distribution, reaction mechanism and catalyst reusability over a series of Cu/MgO catalyst are discussed in our earlier study.28 The carbon balance was 100 ± 5% for all the experimental results reported.


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3. RESULTS AND DISCUSSION 3.1. Effect of reaction parameters This section focused on the kinetic study over 35 wt.% Cu/MgO catalyst. The effect of reaction temperature (190-230oC), pressure (3-6 MPa) and glycerol concentration (20-60 wt.%) was evaluated. Power law and Langmuir-Hinshelwood-Hougen-Watson (LHHW) type model was developed and the experimental data obtained was tried to fit the kinetic models. 3.1.1. Effect of temperature Variation of reaction rate and the product selectivity with reaction time at three different reaction temperatures is shown in Figure 2. The rate of reaction was increased with reaction time as well as reaction temperature. Over 35 wt.% Cu/MgO catalyst, 1,2-PDO and EG were the main products. However, trace amounts (< 5%) of other degradation products such as ethanol, methanol, 1-propanol, 2-propanol and acetol, were also detected depending on the reaction temperature as well as time. 39 At 190oC, after 2 h, 1,2-PDO selectivity was ~95% and it was decreased to ~92% after 12 h. However, at 210oC, 1,2-PDO selectivity was slightly reduced (~89%) after 2 h and further it was almost constant up to 12 h. At higher reaction temperature (230oC), 1,2-PDO selectivity was decreased ~5% after 12 h. For EG, at lower temperature (190oC), selectivity was increased ~3% after 12 h and at higher temperature (>210oC) it showed the decreasing trend. With increasing the reaction temperature, the selectivity to EG was decreased after 12 h of reaction (Figure 2). These results suggested that, higher temperature and longer reaction time facilitated over hydrogenolysis of 1,2-PDO and EG


to degradation


products. Therefore, higher reaction temperature and longer period of reaction time was not beneficial for higher 1,2-PDO selectivity.12,39 3.1.2. Effect of pressure The rate of reaction was increased with reaction time as well as pressure (Figure 3). The reaction rate was increased with hydrogen pressure was due to the high solubility of hydrogen in the reaction mixture and also more availability of hydrogen to be adsorbed on the catalyst surface.37 After 12 h of reaction, the reaction rate was increased from ~7.4×10-3- 5.9×10-2 mol gcat-1 h-1 with increasing the reaction pressure from 3 MPa to 6 MPa. The selectivity to 1,2-PDO and EG were not significantly affected by hydrogen pressure and selectivity of these products were found to be in the range of 90-92% and 5-9%, respectively.21 3.1.3. Effect of glycerol concentration To determine the influence of glycerol concentration on the catalytic activity, the reaction was performed at 210oC and 4.5 MPa hydrogen pressure at various glycerol concentration (20-60 wt.%). The catalyst concentration was kept constant at 8 wt.%. As shown in Figure 4, the reaction rate was decreased at higher glycerol concentration. After 12 h, the reaction rate was decreased from ~6.0×10-2-3.7×10-2 mol gcat-1 h-1 with increasing the glycerol concentration from 20 wt.% to 60 wt.%. At higher glycerol concentration (> 40 wt.%), the rate was decreased significantly due to decreasing the catalyst to glycerol weight ratio.21 In presence of 20 wt.% glycerol, 1,2-PDO selectivity was increased (~1%) with the simultaneous decrease (~3%) in the selectivity to EG after 12 h. At higher glycerol concentration, 1,2-PDO selectivity was decreased significantly (~6%) after 12h. Whereas, the selectivity variation of EG with reaction time was not significant and it was almost close to 5% even after 12 h of reaction. These results suggested 8 ACS Paragon Plus Environment

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that, higher glycerol concentration and longer period of reaction time was not effective for higher selectivity to 1,2-PDO.7,12,37 3.2. Effect of external mass transfer, intra-particle diffusion and heat transfer limitation To ascertain the absence of external mass transfer limitation, the experiments were conducted at standard reaction condition at different stirring speeds (500-900 rpm). Product samples were collected after every 2 h interval for 12 h. The results reported in Table 1 suggested no significant change in glycerol conversion and initial reaction rate data at 700 rpm and higher. Therefore, all the experimental data were collected at 700 rpm and external mass transfer resistance was assumed to be negligible. Similar kind of approach to eliminate the external mass transfer effects were also reported previously.9,12,36,37 Wiesz-Prater criterion (φ) was calculated to determine the effect of internal diffusion resistance. The intrinsic reaction rate to internal diffusion rate was represented by the dimensionless parameter ‘φ’ as follows:

ϕ=

robs ρp R p2 D e C AS

(1)

where, robs was the observed reaction rate, ρp was the true density of the catalyst, Rp was the radius of the catalyst particle, De was the effective diffusivity, and the reactant concentration at the catalyst particle surface was CAS. Based on Wiesz-Prater criterion, internal diffusion can be neglected if φ ≤ 1. In the present study, the calculated value of ‘φ’ was found to be 2.3 × 10-3, which suggested the absence of intra particle diffusion resistance.



For heat transfer limited reaction, it is well known that the rate of reaction increase exponentially with temperature, and a small variation of reaction temperature greatly influence the observed reaction rate.40 For all the experiments performed in this study, no significant variation of reaction temperature was observed although the hydrogenolysis of glycerol reaction is known as exothermic in nature (∆Hrxn = -103 kJ/ mol). This result suggested the absence of heat transfer resistance. 4. KINETIC MODEL DEVELOPMENT Power law and Langmuir-Hinshelwood-Hougen-Watson (LHHW) type model was developed and the experimental data was tried to fit the kinetic models. Power law model was used to determine the preliminary reaction rate parameters. However, Power law approach has major limitation i,e. this model do not include all the factors associated with heterogeneous reaction such as adsorption, desorption and surface reaction on solid catalyst surface. As a result, a model describing the rate equation derived from the reaction mechanism which represents the actual surface phenomena during the reaction is preferred for solid catalysed reactions. Therefore, LHHW model was developed. LHHW model is commonly used realistic approach to derive the rate expression for heterogeneous reactions. The reaction rate derived by this method includes adsorption, desorption and surface reaction steps occurring on the catalyst active surface.40 To develop the kinetic model, glycerol was considered as a limiting reactant since hydrogen was in excess and the reaction rate was a function of concentration of glycerol under constant hydrogen pressure.37


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4.1. Power law model Following Power law model, the overall rate of an irreversible reaction can be expressed by Eq. (3).

Glycerol  catalyst  → Product

r

=

dC G = kC dt

n G

dC G  -E  n CG = k 0 exp  dt  RT 

(2)

(3)

(4)

where, CG is the glycerol concentration at any time, E is the activation energy, T is the reaction temperature, R is the gas constant, n is the order of reaction, k and ko represents specific reaction rate constant and pre-exponential factor, respectively. In order to estimate the kinetic parameters and simulated concentration-time data, rate equation (3) was solved numerically in MATLAB using ode45 function coupled with the genetic algorithm optimization approach by fitting experimental data. The optimum value of the kinetic parameters were determined by minimizing the residual sum of squares between the experimental and model predicted glycerol concentration values for all the experiments. The objective function was defined as: N

f

=

∑

i =1

 (C 

i G ,ex p

− C

i G , s im

)

2

 


(5)


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i where, N represents the number of experiments and C G ,exp is the experimental concentration,

i while C G , sim is the corresponding predicted concentration obtained from the kinetic model.

The apparent reaction order ‘n’ for hydrogenolysis was found to be 1.2 with respect to glycerol.29 Furthermore, Arrhenius equation was used to calculate the activation energy (Figure 5(A)). The calculated activation energy and pre-exponential factor was 84.9 kJ mol-1 and 45.2×107 mol. gcat-1 h-1, respectively. The activation energy and pre exponential factor values reported in the previous literature over different catalysts were compared (Table 2). Experimental and simulated concentration of glycerol is shown in Figure 5(B). The parity plot (Figure 5 (C)) showed good agreement between experimental and model predicted glycerol concentration with R2 value of ~1.

4.2. Langmuir-Hinshelwood-Hougen-Watson (LHHW) model The plausible LHHW type reaction mechanism (Figure 6) was proposed to develop the kinetic model. In this mechanism, it was proposed that glycerol molecules and dissociated hydrogen atom get adsorbed on the active sites of the catalyst surface. In the next step, adsorbed glycerol molecules interacted with the adsorbed hydrogen atom and produced adsorbed 1,2-PDO and EG. Finally, 1,2-PDO and EG were desorbed and the catalyst surfaces were regenerated.29, 37 The rate equations were derived based on the reaction mechanism proposed. Step 1: Adsorption of glycerol (G) on the surface vacant site (S): k

1  → G + S ← 

k −1

G.S

(6)

H .S

(7)

Adsorption of hydrogen on the surface vacant site (S): k

2  → H + S ← 

k −2


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Step 2: Surface reaction between adsorbed glycerol (G.S) and hydrogen atom (H.S) on the active surface of catalyst. k

3  → G . S + H. S ← 

k −3

P. S + W. S

(8)

E.S + S

(9)

k

4  → G . S + H . S ← 

k −4

where, P, E, and W represented 1,2-PDO, EG, and water, respectively. Step 3: Desorption of 1,2-PDO and EG from the catalyst surface and regenerated the vacant site k

5  → P+S P. S ← 

(10)

k −5

k

6  → E+S E. S ← 

(11)

k −6

Along with 1,2-PDO and EG, trace amounts ( K5 > K6, which indicated that glycerol was strongly adsorbed on the active catalytic surface. This strong adsorption of glycerol and comparatively weak adsorption of 1,2-PDO resulted the higher glycerol conversion and higher 1,2-PDO selectivity. The variation of experimental and simulated concentrations with time for glycerol, 1,2-PDO and EG at different temperatures, pressures, and glycerol concentrations are shown in the Figure 7-9. The result showed an excellent fit of the experimental and simulated concentrations. The experimental and predicted concentrations of glycerol, 1,2-PDO, and EG were compared by means of parity plots (Figure 10). For all the products, the deviation of experimental and predicted concentrations was negligible and the correlation coefficients were greater than 0.997 for glycerol and 1,2-PDO. These results demonstrated that the proposed LHHW model consisting of a reaction scheme where two parallel routes for the formation of 1,2PDO and EG from glycerol was satisfactorily able to correlate the experimental data.

5. CONCLUSIONS 35 wt.% Cu/MgO catalyst was prepared by using precipitation-deposition method and the catalytic activity was evaluated for liquid phase hydrogenolysis of glycerol in a high pressure autoclave. The effect of temperature (190-230oC), pressure (3-6 MPa), and glycerol concentration (20-60 wt.%) was evaluated. The kinetic results demonstrated significant variation of glycerol conversion and product selectivity at different reaction conditions. Based on the



reaction products obtained, two parallel routes for the formations of 1,2-PDO and EG from glycerol was proposed. Power law and LHHW type reaction kinetic models were developed and tried to fit the experimental data obtained. To simulate the experimental concentration-time data, the set of differential equations were developed and solved numerically using ode23s in MATLAB coupled with genetic algorithm optimization tool. The kinetic parameters were estimated by minimizing the residual sum of squares between the predicted and experimental concentrations of glycerol, 1,2-PDO and EG. Results demonstrated that Power law and LHHW model proposed, satisfactorily correlated the rate data. Experimental and calculated concentration of glycerol and products (1,2-PDO and EG) showed good fit in the models. From Power law model, the apparent overall reaction order was found to be 1.2 with respect to glycerol. The activation energy and pre-exponential factor were found to be 84.9 kJ mol-1 and 45.2 x 107 mol gcat-1 h-1, respectively. Further, more realistic LHHW model was used to determine the kinetic parameters and compared with the power law model. Equilibrium constants (K1, K2, K3 and K4) and pre-exponential factors (ko) for adsorption and desorption steps were calculated. For LHHW model, the activation energy and pre-exponential factor for the formation of 1,2-PDO was found to be 88.2 kJ mol-1 and 1.1 x 109 mol gcat-1 h-1, respectively.

ACKNOWLEDGEMENTS The author thanks Dean of Sponsored Research & Industrial Consultancy, IIT Roorkee, Uttarakhand, India for funding via SRIC-FUND under FIG (Scheme-A). Authors are thankful to the Department of Science and Technology (DST), Gov. of India for funding under FTYS scheme (SR/FTP/ETA-0032/2011, DATED 21.2.2012). MHRD, Gov. of India for the award of teaching assistanceship to carry out this work is also highly acknowledge. 20 ACS Paragon Plus Environment

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24. Huang, Z.; Cui, F.; Xue, J.; Chen, J.; Xia, C., Cu/SiO2 catalysts prepared by homo and heterogeneous precipitation-deposition method: Texture, structure, and catalytic performance in the hydrogenolysis of glycerol to 1,2-propanediol. Catal. Today. 2012, 183, 42-51. 25. Vasiliadou, E.S.; Eggenhuisen, T.M.; Munnik, P.; deJongh, P.E.; deJongh, K.P.; Lemonidou, A.A., Synthesis and performance of highly dispersed Cu/SiO2 catalysts for the hydrogenolysis of glycerol. Appl. Catal. B: Environ. 2014, 145, 108-119. 26. Balaraju, M.; Rekha, V.; Prasad, P.S.; Prasad, R.B.N.; Lingaiah, N., Selective hydrogenolysis of glycerol to 1,2-propanediol over Cu-ZnO catalysts. Catal. Lett. 2008, 126, (1-2), 119-124. 27. Duran-Martin, D.; Ojeda, M.; Granados, M.L.; Fierro, J.L.G.; Mariscal, R., Stability and regeneration of Cu-ZrO2 catalysts used in glycerol hydrogenolysis to 1,2-propanediol. Catal. Today. 2013, 210, 98-105. 28. Pudi, S.M.; Biswas, P.; Kumar, S., Selective hydrogenolysis of glycerol to 1,2-propanediol over highly active copper-magnesia catalysts: reaction parameter, catalyst stability and mechanism study. J. Chem. Tech. Biotech. 2016, 91, 2063-2075. 29. Lahr, D.G.; Shanks, B.H., Kinetic analysis of the hydrogenolysis of lower polyhydric alcohols: glycerol to glycols. Ind. Eng. Chem. Res. 2003, 42, (22), 5467-5472. 30. Torres, A.; Roy, D.; Subramaniam, B; Chaudhari, R.V., Kinetic modeling of aqueous-phase glycerol hydrogenolysis in a batch slurry reactor. Ind. Eng. Chem. Res. 2010, 49, 1082610835. 31. Xi, Y.; Holladay, J.E.; Frye, J.G.; Oberg, A.A.; Jackson, J.E.; Miller, D.J., A kinetic and mass transfer model for glycerol hydrogenolysis in a trickle-bed reactor. Org. Process Res. Dev. 2010, 14, (6), 1304-1312.


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41. Ameen A.; Mondal S.; Pudi S. M.; Pandhare N. N.; Biswas P., Liquid phase hydrogenolysis of glycerol over highly active 50%Cu-Zn(8:2)/MgO catalyst: reaction parameter optimization by using response surface methodology. Energy & Fuels. 2017, 31, 8521-8533. 42. Maeder, M.; Neuhold, Y.M.; Puxty, G., Application of a genetic algorithm: near optimal estimation of the rate and equilibrium constants of complex reaction mechanisms. Chemom. Intel. Lab. Sys. 2004, 70, (2), 193-203. 43. Moros, R.; Kalies, H.; Rex, H.G., A genetic algorithm for generating initial parameter estimations for kinetic models of catalytic processes. Comput. Chem. Eng. 1996, 20, (10), 1257-1270. 44. Park, T.Y.; Froment, G.F., A hybrid genetic algorithm for the estimation of parameters in detailed kinetic models. Comput. Chem. Eng. 1998, 22, S103-S110. 45. Holland, J.H., Adaptation in natural and artificial systems, The University of Michigan Press, Ann Arbor, MIT, United states, 1975. 46. McCall, J., Genetic algorithms for modelling and optimisation. J. Comput. Appl. Math. 2005, 184, (1), 205-222. 47. Nimlos, M.R.; Blanksby, S.J.; Qian, X.; Himmel, M.E.; Johnson, D.K., Mechanisms of glycerol dehydration. J. Phys. Chem. A. 2006, 110, (18), 6145-6156.

Table captions Table 1. Conversion of glycerol and products selectivity at different stirring speed Table 2. Activation energy and pre-exponential factor over various catalysts Table 3. Estimated kinetic parameter


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Table 1 Conversion of glycerol and products selectivity at different stirring speed 2h

12 h

500 rpm

700 rpm

900 rpm

500 rpm

700 rpm

900 rpm

Glycerol conversion (%)

46.3

47.3

47.8

91.6

96.3

96.4

Selectivity to 1,2-PDO (%)

88.0

89.0

90.5

88.3

92.6

91.7

Selectivity to EG (%)

8.5

6.2

7.5

5.5

5.1

6.0

Selectivity to others b (%)

3.5

4.8

2.0

6.2

2.3

2.3

Reaction rate (mol/gcat-h)

0.02865

0.03106

0.03226

0.0094

0.0101

0.0112

Reaction condition: 20 wt% glycerol, 210oC, 4.5 MPa H2 pressure, 8 wt.% catalyst; b

Other products: acetol, 1-propanol, 2-propanol, methanol, and ethanol.


Industrial & Engineering Chemistry Research 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

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Table 2 Activation energy and pre-exponential factor over various catalysts Sl. No.

Catalyst

1 2

Model used

ko

Reference

Ea (kJ/mol)

(mol/ gcat h)

35 wt.% Cu/MgO

84.9

45.2 × 107

Power law model

This study

Cu0.4/Zn0.6Mg5.6Al2O8.6

65.5

5.6 × 106

Power law model

Xia et al. (2012)

Power law model 6

Vasiliadou and

3

Cu/SiO2

94.3

31.2 × 10

4

Nano fibrous Ag/OMS

114.5

99.9 × 1010

Power law model

Yadav et al. (2012)

5

Cu:Zn:Cr:Zr

131.6

79.1 × 1011

LHHW type model

Sharma et al. (2014)


Lemonidou (2013)

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Table 3 Estimated kinetic parameter

Activation energy, Ea (kJ/mol)

Pre-exponential factor, ko

Formation of glycerol to 1,2-PDO (k3′)

88.2

1.1 × 109 (mol/ gcat h)

Formation of glycerol to EG (k4′)

82.0

1.7 × 107 (mol/ gcat h)

K1

71.3

7.8 × 10-9 (L/mol)

K2

53.2

8.9 × 10-7 (L/mol)

K5

66.7

6.1 × 10-8 (L/ mol)

K6

50.3

5.5 × 10-6 (L/ mol)



Figure captions Figure 1. Autoclave reactor setup Figure 2. Variation of reaction rate (A) and product selectivity (B) with reaction time at different temperatures. Figure 3. Variation of reaction rate (A) and products selectivity (B) with reaction time at different reaction pressures. Figure 4. Variation of reaction rate (A) and product selectivity (B) with reaction time at different glycerol concentrations. Figure 5. (A) Arrhenius plot, (B) concentration-time profile of glycerol at different temperatures, (C) Comparison of experimental glycerol concentration with concentrations predicted by using power law model. Figure 6. LHHW type reaction mechanism for glycerol hydrogenolysis in presence of 35 wt.% Cu/MgO catalyst. Figure 7. Comparison of experimentally observed concentration and simulated concentrations at (A) 190oC, (B) 210oC, and (C) 230oC. Figure 8. Comparison of experimentally observed concentration and simulated concentrations at (A) 3 MPa hydrogen pressure, (B) 6 MPa hydrogen pressure. Figure 9. Comparison of experimentally observed concentration and simulated concentrations at (A) 40 wt.% glycerol as feed and (B) 60 wt.% glycerol as feed. Figure 10. Comparison between experimental concentration and the concentration calculated by using LHHW model.


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Figure 1. Autoclave reactor setup



Figure 2. Variation of reaction rate (A) and product selectivity (B) with reaction time at different temperatures. Reaction condition: glycerol concentration: 20 wt.%, H2 pressure: 4.5 MPa, catalyst: 8 wt.%, rpm: 700 rpm.


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Figure 3. Variation of reaction rate (A) and products selectivity (B) with reaction time at different reaction pressures. Reaction condition: glycerol concentration: 20 wt.%, temperature: 210oC, catalyst: 8 wt.%, rpm: 700 rpm.



Figure 4. Variation of reaction rate (A) and product selectivity (B) with reaction time at different glycerol concentrations. Reaction condition: temperature: 210oC, H2 pressure: 4.5 MPa, catalyst: 8 wt.%, rpm: 700 rpm.


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Figure 5. (A) Arrhenius plot, (B) concentration-time profile of glycerol at different temperatures, (C) Comparison of experimental glycerol concentration with concentrations predicted by using power law model.



Figure 6. LHHW type reaction mechanism for glycerol hydrogenolysis in presence of 35 wt.% Cu/MgO catalyst.


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Figure 7. Comparison of experimentally observed concentration and simulated concentrations at (A) 190oC, (B) 210oC, and (C) 230oC.Reaction condition: glycerol concentration: 20 wt.%, H2 pressure: 4.5 MPa, catalyst: 8 wt.%, rpm: 700 rpm.



Figure 8. Comparison of experimentally observed concentration and simulated concentrations at (A) 3 MPa hydrogen pressure, (B) 6 MPa hydrogen pressure. Reaction condition: glycerol concentration: 20 wt.%, temperature: 210oC, catalyst: 8 wt.%, rpm: 700 rpm.


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Figure 9. Comparison of experimentally observed concentration and simulated concentrations at (A) 40 wt.% glycerol as feed and (B) 60 wt.% glycerol as feed. Reaction condition: temperature: 210oC, H2 pressure: 4.5 MPa, catalyst: 8 wt.%, rpm: 700 rpm.



Figure 10. Comparison between experimental concentration and the concentration calculated by using LHHW model.


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Graphical abstract

7

3.0

Glycerol concentration

0.7

1,2-PDO concentration

EG concentration

6

4 3 2

R =0.9979

R2=0.9832 0.5

2.0

C EG predicted

C 1,2-PDO predicted

5

0.6

2

2.5

R2=0.9987

CGly predicted

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


1.5 1.0

1

0.5

0

0.0

0.4 0.3 0.2 0.1 0.0

0

1

2

3

4

5

6

7

0.0

0.0

0.5

1.0

1.5

2.0

E1,2-PDO = 88.2 kJ mol

OH

0.1

0.2

0.3

0.4

0.5

0.6

CEG experimental

-1

OH

Hydrogen HH

OH Glycerol

3.0

C1,2-PDO experimental

CGly experimental

HO

2.5

(− r3 ) =

HO 1,2-propanediol

k3' CGPH

(1+ K1 CG + K2PH +

CP CE 2 + ) K5 K6

o

35 wt.% Cu/MgO

HH Hydrogen

Temperature: 210 C, Pressure: 45 bar 20 wt.% aqueous glycerol Catalyst loading: 1.6 g

EEG = 82.0 kJ mol

-1

LHHW model

HO

OH Ethylene glycol


(− r4 ) =

k'4 CGPH

(1+ K1 CG + K2PH +

CP CE 2 + ) K5 K6

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