Article pubs.acs.org/IECR
Kinetics of Xylose Dehydration into Furfural in Formic Acid Kaisa Lamminpaä ,̈ * Juha Ahola, and Juha Tanskanen Department of Process and Environmental Engineering, University of Oulu, P.O. Box 4300, FI-90014 Oulu, Finland ABSTRACT: In this study, kinetics of formic acid-catalyzed xylose dehydration into furfural and furfural decomposition was investigated using batch experiments within a temperature range of 130−200 °C. Initial xylose and furfural concentrations up to 0.2 and 0.08 mol/L, respectively, were used. The room temperature pH of the formic acid catalyst solution was between 0.9 and 1.7. The kinetic model used was based on a specific acid catalysis model and included the prevailing hydrogen ion concentration in reaction conditions. The study showed that the modeling must account for other reactions for xylose besides dehydration into furfural. Moreover, the reactions between xylose intermediate and furfural play only a minor role. The study also showed that kinetic modeling of xylose and furfural decomposition reactions must take the uncatalyzed reaction in water solvent into account.
1. INTRODUCTION Biomass, e.g., agricultural residues, is an abundant resource that is readily available worldwide. Lignocellulosic biomass consists mainly of cellulose, hemicellulose, and lignin. The conversion of cellulose and hemicellulose into monomeric sugars, and then further to several products, is a core function of a lignocellulosic biorefinery. Cellulose is a glucan polymer that can be further processed to products such as ethanol, lactic acid, 5hydroxymethylfurfural, levulinic acid, and sorbitol. Hemicellulose is composed of pentose polymers, such as xylan, xyloglucan, and arabinoxylan. In acidic conditions, hemicellulose can be hydrolyzed to monosaccharides, mainly xylose. Other hydrolysis products include arabinose, glucose, mannose and galactose. Xylose and other pentoses may be further dehydrated to furfural, which is a versatile chemical that acts as a starting material for a wide range of chemicals, like furfuryl alcohol and its derivatives, and is also used as a selective solvent that can be used, for example to remove aromatics from lubricating oils.1−3 The kinetics of furfural formation have been studied using xylose as starting material. Arabinose behaves in a similar manner as xylose.1,4 The earliest kinetic models of xylose dehydration date back to the 1940s and 50s, when Root et al.5 and Dunlop6 conducted experiments in sulfuric or hydrochloric acid catalyst with pure xylose. More recently, kinetic studies have been conducted on xylose dehydration using heterogeneous catalysts,7,8 high temperature liquid water medium,9 maleic acid,10 and mineral acids.11,12 Mineral acids are effective catalysts and are used in industrial furfural production. The acid has to either be recovered for its reuse or neutralized, which induces a disposal problem.13 Although various heterogeneous catalysts have been studied for furfural production,7,8,14−18 these are not yet feasible. In addition, biphasic reactors19 and ionic liquids20 have been proposed as an improvement of the processes. The use of formic acid to xylose dehydration has not been studied to a great degree, but it has been shown to be an effective catalyst for furfural formation.21 Furthermore, thermal operation can be utilized in formic acid separation from reaction media. Moreover, formic acid is formed in furfural process via decomposition reactions of hemicellulose and furfural.1,6,22,23 © 2012 American Chemical Society
The organic acid may be most attractive when furfural production is integrated to organosolv fractionation. The present study investigated kinetics of furfural formation and decomposition in formic acid. The kinetic model used is based on a specific acid catalysis model. The kinetic modeling used the prevailing hydrogen ion concentration in reaction conditions.
2. MATERIALS AND METHODS 2.1. Experimental Section. Xylose, furfural, and formic acid were purchased from MPBiomedicals, Acros Organics, and Riedel-de Haën, respectively. All chemicals were used without further purification. Reactant solutions were prepared with varying amounts of xylose (0−0.2 mol/L), furfural (0−0.08 mol/L), and formic acid (7−30 wt-%). Table 1 lists the prepared solutions. Table 1. Initial Reactant Solutions Used in Experiments
a
solution no.
xylose (mol/L)
furfural (mol/L)
pHa
1 2 3 4 5 6 7 8 9 10 11
0.067 0.068 0.071 0.068 0.20 0.20 0 0 0 0.080 0.079
0 0 0.034 0.037 0 0 0.051 0.051 0.053 0.080 0.081
1.70 0.92 1.53 0.92 1.53 0.92 1.53 0.92 0.94 1.57 0.95
At room temperature.
The experiments were carried out using zirconium batch reactors with a volume of ∼40 mL. The temperature of the liquid in each reactor was monitored using a Pt-100 sensor in a Received: Revised: Accepted: Published: 6297
August 17, 2011 February 3, 2012 April 11, 2012 April 30, 2012 dx.doi.org/10.1021/ie2018367 | Ind. Eng. Chem. Res. 2012, 51, 6297−6303
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zirconium pocket. The total volume of the reactor without the temperature sensor pocket is 45 mL. Temperature data with respect to time were recorded. A two-oven-system was used for fast heating and steady temperature control: An oven set at 360−420 °C was used for quick preheating, and a fluidized sand bath was set at the desired reaction temperature. A total of 85 experiments were performed at five nominal temperatures (130, 140, 160, 180, and 200 °C). Figure 1 shows the temperature profiles of eight experiments.
The weight percentage approach does not take into account the change of hydrogen ion concentration due to the temperature dependence of acid dissociation constant. The change in H+concentration is larger with organic acids than with mineral acids. Theoretically, activity-based models provide a thermodynamically sound method for evaluating solution properties. In practice, however, the selection of the necessary excess Gibbs energy model, together with its estimated parameters, will determine the accuracy of this approach. In this study, the hydrogen ion concentration of formic acid was used in kinetic modeling. The temperature dependence was taken into account by eq 1 obtained by Kim et al.,28 which shows the temperature dependence of dissociation constant (pKa) for formic acid. Kim et al.28 studied temperatures from 25 to 175 °C and showed that the calculated pKa is in good agreement with literature values from 0 to 200 °C. pK a = −57.258 + 2773.9/T + 9.1232 ln T
(1)
where T is temperature in K. The H+-concentrations (mol/L) are calculated using a system of nonlinear equations based on restrictions for the system from equilibrium state and material and ion balances. The system of nonlinear equations is presented in eqs 2−4. The initial formic acid concentration, CHCOOH0, at room temperature (23−25 °C) was calculated using the measured pH-values of initial reactant solutions presented in Table 1 and eqs 1−4. H+-concentrations in reaction temperature were calculated using the temperature data of each experiment, eqs 1−4, and the initial formic acid concentration at room temperature.
Figure 1. Temperature profiles of eight experiments. The nominal temperatures of the experiments were 140, 160, 180, and 200 °C.
At the beginning of the experiments, 30 mL of reaction solution was pipetted in each reactor and the reactors were then sealed and weighed. The experiment started when the reactor was put into the preheating oven. The reactor was heated until the temperature inside the reactor was 20−25 °C below the desired reaction temperature. The reactor was then inserted to the fluidized sand bath. The total heating time, in which the desired reaction temperature was achieved, varied from 3 to 4 min. After the desired reaction time, the reactors were cooled in a cold water bath. A sample of 10 mL was taken for composition analysis and the rest of the solution was used for pH measurement. Concentrations of xylose and furfural in the experimental samples were analyzed by HPLC. The samples were filtered prior to analysis. The column was Coregel 87H3 (7.8 mm ID × 300 mm). The HPLC was operated at the temperature of 60 °C and eluted with 0.8 mL/min flow of sulfuric acid (0.01 N). Calibration curves were based on 4 calibration points. The calibration chemicals were purchased from Merck. A different set of chemicals was used to prepare calibration verification standards. The pH of the experimental samples as well as initial solutions was measured using a SenTix 81 pH electrode (WTW) with a temperature probe for temperature compensation. The electrode was connected to an inoLab pH 720 meter (WTW). The pH meter was calibrated using three DIN buffer solutions (1.679, 4.008, and 6.865). The calibration was verified using buffer solutions of pH 0.99 and 2.00. The pH values were measured with an accuracy of 0.01. 2.2. Calculations of H+-Concentrations. The xylose dehydration and furfural decomposition are hydrogen ion catalyzed reactions and the reaction rates depend on the catalyst amount. The amount of homogeneous acid catalyst is usually taken into the kinetic model in hydrogen ion concentration,5,23 in weight percentage,11,24−26 or in activity.4,27
C H +C HCOO − − C HCOOHK = 0
(2)
C HCOOH0 − C HCOOH − C HCOO − = 0
(3)
C H + − C HCOO − = 0
(4)
where CH+, CHCOO‑ and CHCOOH are concentrations (mol/L) in equilibrium state of dissociation and K is equilibrium constant, K = 10−pKa. Figure 2 shows the variation of pH during experiments at two different temperatures.
Figure 2. pH profile of two experiments with nominal temperatures of 140 and 200 °C. The pH in room temperature was 0.92.
2.3. Formic Acid Decomposition. Formic acid decomposes at high temperatures, producing either carbon monoxide and water or carbon dioxide and hydrogen. The decomposition could have an effect on the estimated H+-concentrations. Kupiainen et al.29 have studied formic acid decomposition in temperatures between 180 and 220 °C using 5 to 20 wt % 6298
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reference temperature T mean, C H is the hydrogen ion concentration in reaction temperature, T is reaction temperature, and Ei is activation energy. The reactions of the model are assumed to follow the rate equations for similar elementary reactions. When the reactions are carried out in a batch reactor, the component mass balance for model A based on Scheme 1 are in eqs 7 and 8; in eqs 9−11 for model B (Scheme 2), and in eqs 7, 10 and 11 for model C (Scheme 3).
formic acid solutions. The maximum formic acid conversion detected was 2% after a reaction time of 156 min in a batch reactor at 180 °C. Accordingly, it was concluded that formic acid decomposition does not have a notable effect on the kinetics of furfural formation. However, the pH of samples before and after the reaction were measured and there was no difference in the measured pHs. 2.4. Kinetic Modeling. The kinetic modeling of furfural formation in this study was based on three different schemes. Scheme 1 had direct xylose decomposition, Scheme 2 had a side reaction between xylose-intermediate and furfural, and Scheme 3 combines schemes 1 and 2. Scheme 1. Furfural Formation with Direct Xylose Decomposition
dCX = −k1C X − k 3C X dt
(7)
dCF = k1C X − k 2C F dt
(8)
dCX = −k1C X dt
(9)
dCF = k4C I − k 2C F − k5C IC F dt
Scheme 2. Furfural Formation with Side Reaction between Intermediate and Furfural
dCI = k1C X − k4C I − k5C IC F (11) dt where k1, k2, k3, k4 and k5 are rate constants and CX, CF, and CI are concentrations (in mol/L) for xylose, furfural, and intermediate, respectively. The recorded temperature data with respect to time was used in estimation. Thus, explicit energy balance equation is not needed in the kinetic modeling despite the nonisothermal experimental condition. The model equations were implemented in a MATLAB environment. The system of ordinary differential equations (ODEs) was solved numerically by ODE15S, a solver for stiff systems that is based on the numerical differentiation formulas. The kinetic parameters were estimated using nonlinear regression analysis. The estimation was done by the Levenberg−Marquardt algorithm available within MATLAB’s LSQCURVEFIT function.
Scheme 3. Furfural Formation with Direct Xylose Decomposition and Side Reaction with Intermediate
Previous kinetic studies1,5,6,9,12,24,30 had used either Scheme 1 or 2. These studies were conducted with sulfuric or hydrochloric acid or with water solvent at temperature range from 140 to 280 °C. In the specific acid−base catalysis the rate constant can be expressed as given in eq 5.31 Each term has its own activation energy. k = k 0 + kHC H + k OHCOH
3. RESULTS AND DISCUSSION 3.1. Kinetic Modeling of Furfural Destruction. First, furfural decomposition was studied without the presence of xylose. Furfural can react with itself, forming polymeric resins. Furfural destruction to smaller molecules can also occur in the studied conditions. In this study, these both reaction pathways are referred to as furfural decomposition. Figure 3 shows the
(5)
where k0 is the rate constant for the uncatalyzed reaction; kH and kOH are the rate constants for catalysis by hydrogen ions (H+) and hydroxide ions (OH−), respectively; CH is the hydrogen ion concentration; and COH is the hydroxide ion concentration. In this case, the eq 5 can be simplified. Because CH ≫ COH, the base term has no influence on the reaction. Also, it was assumed that the activation energies for k0 and kH are the same. In addition, the common reparametrization, which used the reaction rate constant in the reference temperature instead of the pre-exponential factor, was utilized to reduce the correlation between the estimated parameters. Thus, the rate constant is represented as follows: ki = (k 0, i + kH, iC H)e
−Ei / R( 1 − 1 ) T Tmean
(10)
(6)
Figure 3. Furfural concentration with time as −ln(CF/CF0) versus t in three temperatures (■ 160 °C, ● 180 °C, ▲ 200 °C) and two pHs (pH 0.92 with black markers; pH 1.53 with white markers).
where k0,i is the rate constant of uncatalyzed reaction in water solvent and kH,i is the rate constant of acid catalyst (H+) in the 6299
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Table 2. Kinetic Parameters k0a(s−1) furfural destruction model A model B
model C
a
−3
(1) (3) (1) (4) (5) (1) (3) (4) (5)
kHa(dm3/mols) −5
3.6 × 10−3 ± 6 × 10−4 0.25 ± 0.02 0.11 ± 0.02 0.36 ± 0.01 19.0 ± 4.4 52 ± 12 0.25 ± 0.01 0.11 ± 0.01 68 ± 30 8±5
1.0 × 10 ± 4 × 10 2.5 × 10−3 ± 4 × 10−4 5 × 10−4 ± 3 × 10−4 3.3 × 10−3 ± 3 × 10−4 0 0 2.8 × 10−3 ± 2 × 10−4 7 × 10−4 ± 2 × 10−4 0 0
E(kJ/mol) 75.5 152 161 153 144 143 155 147 142 235
± ± ± ± ± ± ± ± ± ±
4.3/135 ± 12b 3.8 7.9 2.1 26 23 2.7 8 49 37
Rate constants are given in reference temperature of 165 °C. bSeparate activation energies for solvent and acid terms shown in eq 13.
°C). However, earlier studies5,22,32 conducted with sulfuric or hydrochloric acid reported much lower values for activation energies. The reported values are 83.6 kJ/mol22 and 92.4 kJ/ mol5 for sulfuric acid and 48.1 kJ/mol32 for hydrochloric acid. Marcotullio et al.27 used ion activities estimated by the electrolyte NRTL model to account for the variation of H+concentration with temperature. They chose the activities (k* = kaH3O+), because use of H+-concentration (k* = k[H3O+]) did not fit satisfactorily with Arrhenius formulation. The present study adopted a different approach for temperature dependence, shown in eq 13. Nevertheless, the H+-concentration and activity based approaches and the results with no added catalyst are in good accordance with each other. It seems reliable that water solvent has an effect on furfural decomposition in spite of the used catalyst. Therefore, kinetic modeling must take the uncatalyzed reaction in water solvent into account in some way. 3.2. Kinetic Modeling of Xylose Decomposition and Furfural Formation. The kinetic parameters for xylose decomposition and furfural formation were estimated separately for the three models. In each case, the parameter values for furfural decomposition, which were estimated in the absence of xylose, were used. A relatively good fit was achieved for each model. The concentration based residual sum of squares for the models A, B, and C was 0.00560, 0.00607, and 0.00565, respectively. This results the coefficient for determination (R2) around 99.4% in all three models. The parameters k0,4 and k0,5 in the models B and C were not identified, so the values were set to zero. The parameter k4 in model C was one side identified: magnification of the parameter after a certain point had no notable effect on the object function. The kinetic parameters for xylose dehydration (k0,1, kH,1 and E1) are nearly the same in all three models, which causes the models to provide almost identical prediction for xylose conversion. In addition, the parameter values for xylose decomposition (k0,3, kH,3 and E3) are nearly the same despite the used model. Table 2 lists the parameter values with a 95% confidence interval based on the t-distribution. Figures 5, 6, and 7 show the parity plots of xylose conversion, furfural yield, and furfural selectivity as well as xylose and furfural concentrations for different models. The parity plots of concentrations (Figures 5b, 6b, and 7b) only differ slightly from each other. However, there is a clear distinction between the parity plots in Figures 5a, 6a, and 7a. The major difference between the models is in furfural selectivity. Model A fits best to selectivities, whereas model B gives the most scattered prediction for furfural yield and selectivity. This indicates that the form of Schemes 1 and 3 describes the reaction system better than the form of Scheme 2.
furfural concentration with time as −ln(CF/CF0) versus t. Figure 3 reveals that furfural decomposition is a first-order reaction. Thus, the model equation is as follows:
dCF = −k 2C F dt
(12)
where k2 is rate constant and CF is furfural concentration. Moreover, Figure 3 indicates that the rate constant, k2, is dependent on both temperature and pH. The pH has a greater effect on reaction rate when temperature rises; therefore, independent activation energies for uncatalyzed and acid catalyzed terms were required in the rate constant equation. Consequently, temperature dependence, as shown in eq 13, was used. ki = k 0, ie
−E0, i / R( 1 − 1 ) T Tmean
+ kH, iC He
−E H, i / R( 1 − 1 ) T Tmean
(13)
where E0,i and EH,i are activation energies. The kinetic parameters for furfural decomposition were estimated from the experiments with aqueous furfural in two acid concentrations. Table 2 shows the parameters. The coefficient of determination (R2-value) was 99.99%. The conversions of furfural varied from 0.8% to 18%. The conversion profiles are shown in Figure 4, from which it can be seen that the model fits the experimental data correctly.
Figure 4. Conversion profiles of furfural destruction in two initial pHs and three temperatures and experimental points (pH 0.92/1.53 in 200 °C ⧫/◊, 180 °C ■/□ and 160 °C ●/○).
The estimated activation energies are in good agreement with the values given by Jing and Lü9 and Marcotullio et al.27 The activation energy for the uncatalyzed reaction (E0) is similar to the value (58.84 kJ/mol)9 obtained with no added catalyst. The activation energy for acid term (EH) is similar to the value (125.1 kJ/mol) obtained by Marcotullio et al.,27 who studied furfural destruction in sulfuric acid (pH 0.81−1.36 at 25 6300
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Figure 5. (a) Parity plot of xylose conversion (*), furfural yield (◊), and selectivity (□) in percentages; and (b) parity plot of furfural (*) and xylose concentrations (□) in mol/L using model A.
Figure 6. (a) Parity plot of xylose conversion (*), furfural yield (◊) and selectivity (□); and (b) parity plot of furfural (*) and xylose concentrations (□). Model B was used.
Figure 7. (a) Parity plot of xylose conversion (*), furfural yield (◊) and selectivity (□); and (b) parity plot of furfural (*) and xylose concentrations (□) using model C.
The conversion and yield profiles predicted by the models were illustrated. The figures showed that all models predicted xylose conversion properly. Models A and C gave a realistic picture of furfural yield in all conditions. The prediction by model B was poor in the experiments done with dilute xylose solutions or with solutions containing the same molarity of xylose and furfural, especially in high temperatures. As an example, Figures 8−11 show the conversion and yield profiles drawn with model A as well as measured xylose conversion and furfural yield points. As Figures 8 and 10 show, adding furfural to the initial solution has no effect on xylose conversion. Nevertheless, increasing furfural amount in input causes diminution in furfural yield (Figures 9 and 11). Moreover, the figures show that when complete xylose conversion is achieved, furfural yield collapses due to furfural decomposition. The effect on furfural
Figure 8. Xylose conversion in initial pH 0.92 and temperatures of 160, 180, and 200 °C. Model A and experiments with initial solutions containing only xylose [initial solutions 2(/△) and 6(−/○)] or xylose and furfural [initial solutions 4(---/□) and 11(···/◊)]. 6301
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other minor products are formed from the acyclic xylose, while furfural and some minor products are formed from the xylopyranose. In the present study, only furfural, formic acid, and xylose were analyzed from the samples. The HPLC analysis did not identify any significant amount of soluble byproduct. However, there was a considerable formation of solid byproduct, especially when the xylose conversion was high. It is also notable that there is an uncatalyzed effect for xylose dehydration and composition besides furfural decomposition. In the case of reactions with xylose intermediate and furfural, however, there are no signs of uncatalyzed reaction. This means that when the H+-concentration in reaction media rises, the intermediate reactions might increase significantly. However, the kinetic models based on Schemes 1 and 3 performed equally well in the studied range of conditions. There are some differences in the borders of the range and, when studying these areas one can be better than the other. Altogether, model A, which has no interactions between xylose intermediate and furfural, is good enough to predict furfural formation from xylose. If the formation of side-products from xylose decomposition or condensation is examined, then a more complicated model (model C) would be needed.
Figure 9. Furfural yield in initial pH 0.92 and temperatures of 160, 180, and 200 °C. Model A and experiments with initial solutions containing only xylose [initial solutions 2(/△) and 6(−/○)] or xylose and furfural [initial solutions 4(---/□) and 11(···/◊)].
4. CONCLUSIONS Formic acid-catalyzed decomposition of xylose, including formation and decomposition of furfural, was studied in a temperature range of 130−200 °C. A simple scheme with direct xylose decomposition, in addition to xylose dehydration to furfural and furfural destruction (Scheme 1), worked well in kinetic modeling. On the basis of this study, it is clear that the modeling must take other reactions for xylose besides furfural formation into account. Moreover, the reactions between xylose intermediate and furfural play only a minor role. Therefore, the scheme with side reaction between xylose-intermediate and furfural (Scheme 2) is not adequate for kinetic modeling. Also, a more complicated model based on Scheme 3 that combines Schemes 1 and 2 was used. It did not show substantially better performance than the model based on Scheme 1 in studied reaction conditions. The study also showed that the pH of the reactant solutions has more effect on reaction rate of furfural decomposition when temperature rises. Thus, the effect of uncatalyzed reaction in water solvent has to be taken into account in kinetic modeling. There is also an uncatalyzed reaction part for xylose dehydration and composition. However, reactions with xylose intermediate and furfural showed no signs of uncatalyzed effects. Therefore, when more concentrated acids are used, the intermediate reactions may become significant.
Figure 10. Xylose conversion in initial pH 1.53 or 1.70 and temperatures of 160, 180, and 200 °C. Model A and experiments with initial solutions containing only xylose [initial solutions 1(/△) and 5(−/○)] or xylose and furfural [initial solutions 3(---/□) and 10(···/◊)].
Figure 11. Furfural yield in initial pH 1.53 or 1.70 and temperatures of 160, 180, and 200 °C. Model A and experiments with initial solutions containing only xylose [initial solutions 1(/△) and 5(−/○)] or xylose and furfural [initial solutions 3(---/□) and 10(···/◊)].
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AUTHOR INFORMATION
Corresponding Author
yield seems to increase with the amount of furfural added to the reaction media. It can be deduced from the figures that the decomposition reactions of furfural impact more on the yield than reactions between xylose intermediate and furfural. Models A and C have a competitive reaction path for xylose besides dehydration to furfural, while model B does not. On the basis of kinetic modeling, the other reaction path for xylose seems to be important. Antal et al.23 suggested that the different forms of xylose (acyclic, furanose and pyranose rings) react in different ways. They proposed that pyruvaldehyde and some
*Tel.: +358 8 553 2333. Fax: +358 8 553 2304. E-mail: kaisa. lamminpaa@oulu.fi. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS Financial support from the Academy of Finland is greatly appreciated. 6302
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dx.doi.org/10.1021/ie2018367 | Ind. Eng. Chem. Res. 2012, 51, 6297−6303
