Kinetic Analysis of Methanol to Dimethyl Ether Reaction over H-MFI

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Kinetic Analysis of Methanol to Dimethyl Ether Reaction over H‑MFI Catalyst Massimo Migliori,* Alfredo Aloise, Enrico Catizzone, and Girolamo Giordano University of Calabria, Department of Environmental and Chemical Engineering, Via P. Bucci Cubo 44a, I-87036 Rende CS, Italy S Supporting Information *

ABSTRACT: This paper reports the kinetic analysis of methanol dehydration to dimethyl ether (DME) on a zeolitic MFI-type catalyst. For this reaction, γ-alumina is the most used catalyst, but the use of a zeolite, such as H-MFI, is gaining greater attention because these materials exhibit a better stability against water presence and can modulate the catalyst acidity acting on different parameters (e.g., Si/Al ratio or postsynthesis treatments). The kinetic analysis of H-MFI is performed by using experimental data of methanol conversion in a differential reactor and in an integral reactor. By including the most important kinetic models proposed in the literature for alumina, kinetic parameters (as a function of temperature) in the case of H-MFI are calculated, and the comparison between different models is also presented and discussed. In addition a new kinetic model is proposed and data fitting is preferable with respect to literature equations: also data of activation energy are in agreement with literature findings.

1. INTRODUCTION Scientific research in the energy field has been focusing on individuating and testing renewable and alternative energy sources as well as on the development of sustainable energy conversion processes. Compared to some of the other leading alternative candidates as fuel alternatives (such as hydrogen, ethanol, methanol), dimethyl ether (DME) appears as a reliable option because it can be produced from nonfossil feed stocks, but also for its high well-to-wheel greenhouse gas emissions, great well-to-wheel efficiencies, versatility, and safety.1 DME, the simplest ether, is a colorless, nontoxic, noncorrosive, noncarcinogenic, and environmentally friendly compound with a normal boiling point of −25 °C that can be liquefied above 0.5 MPa at room temperature.2 DME chemical and physical properties are similar to LPG and the open literature suggested that the technologies developed for storage and transport of LPG can be easily converted to accommodate DME.3 In addition, DME is also an important chemical intermediate to produce widely used chemicals, such as diethyl sulfate, methyl acetate, and light olefins.4 In recent years, dimethyl ether production has received greater attention because of its high cetane number (>55), and important reduction of NOx, SOx e PM emissions in exhaust gases, when used in diesel engines.2 DME can be industrially synthesized in two ways: following the indirect or direct synthesis mechanism. Indirect synthesis is a two-step process: the first step is the traditional methanol synthesis from syngas (H2−CO mixture) over ACZ (Cu/ZnO/ Al2O3) redox catalyst in the temperature range of 240−280 °C, pressure between 3 and 7 MPa and H2/CO ratio range between 0.5 and 2.0, followed by a methanol dehydration reaction to dimethyl ether over acid catalyst.3 DME can be also produced by a one-step process (direct synthesis) in which the methanol synthesis (by CO or CO2 hydrogenation) and the following dehydration to DME take place in the same reactor under process conditions close to those of methanol synthesis.5 Compared to the double step synthesis, because of the reduced © XXXX American Chemical Society

costs, the direct synthesis is a very promising process and a major interest comes from the potential usage of carbon dioxide as DME synthesis reactant.6 The process takes place over a bifunctional catalyst, including both the ACZ catalyst for the methanol synthesis and the acidic function for the dehydration. Different techniques (coprecipitation or mechanical mixtures) have been proposed in the literature to simultaneously obtain the two catalytic functions. Many studies were conducted over γ-Al2O3 as acid catalyst for methanol dehydration in the temperature range of 200−300 °C7−10 showing the high selectivity of this catalyst. Nevertheless, the presence of water, a reaction product, significantly deactivates the catalyst, an effect of the water molecules blocking the active sites.8 In this concern, it has also been reported that the apparent activation energy of the reaction increases when water is added to the reaction stream, and the increase amount is equal to the adsorption heat of water over this catalyst.7 Also other acid catalysts were tested for this reaction, with a wide focus on zeolites, particularly H-MFI.11−15 Owing to the versatility of its acidic properties, high activity even at lower temperature and, most important, stability in the presence of water better than γ-Al2O3, H-MFI is a promising catalyst for methanol dehydration in industrial applications. In fact, the amount, type, and strength of acid sites, activity, selectivity, and kinetic factor depend on different parameters of the zeolites: Si/Al ratio,16 calcination temperature,7 or counterion type and content.15 In addition, with respect to γAl2O3, H-MFI revealed a better stability against the water presence as the hydrophobicity is a characteristic parameter of this zeolite that depends on the acidity.11−13 On the other side, it is well-known that H-MFI is active in the reactions scheme converting methanol to gasoline (MTG process);17 therefore Received: July 14, 2014 Revised: September 10, 2014 Accepted: September 10, 2014

A

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Figure 1. Scheme of the experimental apparatus for catalytic test.

porosimetry data obtained using nitrogen adsorption at 77 K (ASAP 2020 Micromeritics), after a pretreatment in vacuum at 200 °C for 12 h. From the same test, also the micropores volume was estimated. The catalyst was formed in pellets by using a hydraulic pellet press (Graseby Specac, UK) at 2 ton/cm2 pressure for 10 min. The pellet was crushed and then the different size fractions were separated by sieved procedure. 2.2. Experimental Setup. The catalytic test apparatus is shown in Figure 1. Nitrogen, acting as carrier under moderate overpressure, was bubbled through liquid methanol in a thermostatic bath (Julabo F12-ED) by controlling the carrier flow rate via a mass flow controller (Bronkhorst). The methanol molar fraction in the feed stream was regulated, according to its vapor pressure (PM0), by varying the bath temperature in the range −2 to 15 °C, corresponding to a methanol molar fraction in the feed stream yM,0 in the range 0.03−0.088. The vapor phase dehydration of methanol was carried out at steady state conditions in a vertical reactor (Pyrex vessel, i.d. = 15 mm and length = 40 mm) where the catalytic bed was held by a porous septum (pores diameter below 2 μm). Before any test, the freshly loaded catalyst sample was dried under nitrogen flow at 200 °C for 3 h. The composition of the stream leaving the reactor was analyzed by using GC (Agilent 7890 A) equipped with a specific column (J&W 125-1032) and a FID detector. The reaction was investigated between 145 and 190 °C, since in this temperature range the yield in DME is unitary. At higher temperatures, a loss of catalyst selectivity toward DME was observed, because of the consecutive reactions leading to the formation of other light hydrocarbons. 2.3. Kinetic Analysis. The reaction mechanism follows a classical scheme of reactant-adsorption/surface-reaction/product-desorption, and all the kinetic models include the effect of reactant and products concentration.20,21 The kinetic analysis was completed by following two different experimental plans: a differential approach (i.e., low reactant conversion) in order to estimate the kinetic constants related to the reactant then an integral approach was adopted, increasing the methanol conversion, in order to evaluate the kinetic parameter of the reaction products. In the differential approach, 60 to 80 mg of catalyst were loaded in the reactor and the initial methanol flow rate FM,0 was varied between 3.3 mmol/h and 15.5 mmol/h, keeping the methanol fractional conversion in the range 0.02− 0.15.20 As consequence, the nitrogen flow rate FC was set

alcohol dehydration can proceed forward leading to unsaturated hydrocarbons ending in coke formation. This phenomenon is more evident when the catalyst acidity is increased, and it could be relevant in the single step process as the methanol synthesis and MTG temperature ranges are quite well overlapped. Therefore, the acid catalyst should be carefully selected accounting for both water stability and acidity, also because it has been demonstrated that the acid properties of dehydrating catalyst determines the controlling rate of DME synthesis overall. 18,19 For these reasons a preliminary investigation of the single-methanol dehydration is always suitable in order to determine the acid catalyst activity and optimal operating conditions. In addition, to design the reactor, a kinetic equation is needed especially when coping with the controlling step of a series of reactions. A wide literature of kinetic studies is available for γ-Al2O3,20−24 and many kinetic equations have been defined and the related kinetic parameters have been calculated. On the contrary, despite MFI being an attractive alternative to γ-Al2O3 in DME production, only few authors report a kinetic analysis of this catalyst.25,26 The aim of this work was to contribute in this direction, by performing a catalytic test focused on the determination of an intrinsic rate equation for methanol dehydration over H-ZSM-5 at a fixed Si/ Al ratio.

2. EXPERIMENTAL SECTION 2.1. Catalyst Preparation. The catalyst was prepared by using the gel composition reported below and following the preparation procedure described elsewere:16 0.1Na 2O‐0.08TPABr‐1SiO2 ‐0.02Al 2O3‐20H 2O

The sample was calcined at 550 °C for 8 h and a double proton exchange procedure was performed by heating at 80 °C in 1 mol/L aqueous solution of NH4Cl (100 mL per gramcatalyst). The ammonia was then eliminated by calcination at 550 °C, obtaining the final H-MFI form. The sample structure was determined via X-ray powder diffraction (APD 2000 Pro), revealing the typical MFI pattern. The morphology of the crystalline phase was observed on a scanning electron microscope (FEI model Inspect) and the Si/ Al ratio in the structure was measured by ICP-MS (PerkinElmer DRC-e). The specific surface area of the catalyst was calculated by performing a Brunauer−Emmett−Teller (BET) analysis on B

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Table 1. Summary of Physical and Chemical Properties of the H-MFI Zeolite Catalyst Si/Al [mol/mol]

Al/u.c. [-]

BET [m2·g−1]

micropore volume [cm3·g−1]

average crystal size [mm]

37

2.5

350

0.11

4.5

0.95 confidence level and if Q > Fc, model B is statistically preferred to model A.

between 40 and 60 N mL/min, resulting in a weight hourly space velocity (WHSV) between 1.3 and 8.3 h−1. The methanol dehydration rate for unit of catalyst mass −rM [mol/(gcat h)] was calculated from the general isothermal reactor design equation in the differential form:

⎛ W ⎞ dx ⎟⎟ = M d⎜⎜ F ⎝ M,0 ⎠ −rM

3. RESULTS AND DISCUSSION 3.1. Catalyst Properties. The results of the physical and chemical characterization of the catalyst are summarized in Table 1. The adsorption isotherm is shown in Figure S1 (Supporting Information) revealing a typical Type IV shape. All the physical and chemical properties are well in the typical range for a MFI-type zeolite, including the aluminum content per unit of cell (Al/u.c.). 3.2. Internal and External Resistances. As preliminary test the internal and external mass transfer resistances in the reaction system were verified27 at the maximum operating temperature (i.e., 190 °C) because the reaction kinetic is usually the more sensitive phenomenon to temperature variations, as mass and heat transfer rates decrease less rapidly than reaction rates when the temperature decreases. Therefore, the adoption of the highest investigated temperature obeys the conservative criterion. The internal mass transfer resistances were checked by performing a reaction with 80 mg of catalyst at three particle size ranges: namely 150−300 μm, 300−500 μm, and 500−710 μm. The methanol vapor fraction in the feed was 0.08, and the carrier flow was maximized (90 N mL/min) in order to reduce the external resistances. The results, presented in Table 2, show

(1)

where xM is the fractional conversion, calculated from the methanol flow rate FM coming out from the reactor: FM,0 − FM

xM =

FM

(2)

At low value of xM (differential reactor assumption) the initial reaction rate was calculated by direct integration of eq 1: −rM,0 = xM

W FM,0

(3)

The reaction rate data can be directly used in order to evaluate by linear regression the methanol parameter for any tested model as a function of temperature. On the contrary, when an integral approach is followed, the solution of eq 1 requires the complete form of the kinetic equation (including the products contribution) as a function of the methanol conversion: W = FM,0

∫0

xM

dx M −rM

Table 2. External and Internal Resistances Estimation (4)

catalyst pellet size [μm] internal resistances

Therefore, complete isothermal curves of methanol conversion vs W/FM,0 (ranging between 5.7 and 19 g·h/mol) were obtained, and a numerical fit was used to optimize the model parameters related to products, including the reactant parameters calculated in the differential reactor experiments. 2.4. Model Discrimination. To discriminate among different kinetic models applied over the same set of experimental data, a statistical criterion has been adopted, based on the F-test. For two models A and B to be compared, having the parameters number PA and PB respectively, the degree of freedom (DOF) are DOFA = N − PA and DOFB = N − PB, where N is the number of experimental observations yi (i = 1 ..., N). For any model, having the same number of parameters and degree of freedom, the statistical variable Q, having a Fisher probability distribution function with (DOFA, DOFB) degree of freedom, was calculated as follows: Q=

SSA SSB

external resistances

n

(5)

n

∑ [yi − fA (xi , PÂ )]2 SSB = ∑ [yi − fB (xi , PB̂ )]2 i=1

56 73 90

0.157 ± 0.009 0.141 ± 0.009 0.165 ± 0.006 xM [-] 0.137 ± 0.010 0.132 ± 0.011 0.141 ± 0.009

that the methanol conversion does not depend on catalyst particle size and the internal diffusion can be neglected. The particle size was fixed in the range 300−500 μm for the remainder of the work. The influence of external mass and heat transfer was verified by varying both the carrier flow rate and the catalysts weight, keeping a constant value of the contact time W/FM,0. By loading 50, 65, and 80 mg of catalyst and keeping a carrier flow rate of 56, 73, and 90 N mL/min, respectively, a W/FM,0 of 3.8 gcat·h/mol was fixed. Results of catalytic tests in these conditions, reported in Table 2, show that, for a constant values of contact time, xM is nearly independent from the carrier flow rate; therefore the external resistances do not affect the reaction kinetic. 3.3. Kinetic Data. According to the condition described in section 2.3, a set of 24 tests was completed and both experimental conditions and data are reported in Table S1 (Supporting Information). The methanol conversion was measured in three independent steps and the average value ± the standard deviation was calculated. It clearly appears that the

and SSA and SSB are defined as SSA =

150−300 300−500 500−710 W/FC [NmL/min]

xM [-]

i=1

(6)

where f is the estimated value of the observation yi, calculated by assuming the estimated value of the parameters P̂. The Q value is compared to the Fisher function distribution value Fc at C

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methanol conversion was kept in a range (maximum value below 0.13) that allows the assumption of a differential reactor. As a consequence, the measured reaction rate only depends on the methanol initial concentration as the product formation can be neglected. Furthermore, the kinetic of this reaction may also depend on both products (water and DME) concentration and the differential approach, based on pure reactant feed, does not provide data to establish a complete kinetic model. On the other hand, it is well-known20 that DME concentration does not affect the reaction rate, and its contribution can be neglected in any kinetic equation, therefore only the effect of water has to be accounted. Water plays a relevant role in this reaction and its contribution has to be carefully evaluated by performing experiments in which high methanol conversions are achieved and, as expected, water formation affects the reaction rate. For this purpose, by varying the catalysts amount and carrier flow from 60 to 140 mg and 30 to 60 N mL/min, respectively, a different set of tests was carried out. Fixing a constant methanol molar fraction of 0.063, the W/FM,0 value ranged between 5.7 and 19 gcat·h/mol, and the xM values are plotted in Figure 2 as a

Table 3. Investigated Kinetic Models, Model VII Is Proposed As Reported in Section 3.3 number

model

I28

− rM =

k(KMPM)2 (1 + KMPM + KW PW )

II20

− rM =

k(KMPM)2 (1 + 2 KMPM + KW PW )4

III29

− rM =

kKMPM (1 + 2 KMPM + KW PW )2

IV30

− rM =

V31

− rM =

kKMPM (1 + KMPM + KW PW )2

VI28

− rM =

2 kKMPM (1 + 2 KMPM + KW PW )3

VII

− rM =

2 k1PM 2 [1 + k 2(PM) + k 3PW ]4

kKM PM (1 + KM PM + KW PW )

k = k 0e Eak /(RT )

(6)

where Eak [J/(g mol)] is the reaction activation energy. KM and KW are the adsorption constant of methanol and water, respectively, depending on temperature according to the Van’t Hoff equation: ⎡ −ΔHads,M ⎛ 1 1 ⎞⎤ KM(T ) = KM(T0) exp⎢ ⎜ − ⎟⎥ ⎢⎣ R T0 ⎠⎥⎦ ⎝T ⎡ −ΔHads,W ⎛ 1 1 ⎞⎤ KW (T ) = KW (T0) exp⎢ ⎜ − ⎟⎥ ⎢⎣ R T0 ⎠⎥⎦ ⎝T

(7)

where ΔHads [J/g mol] is the heat of adsorption and T0 [K] is a reference temperature, assumed as the lowest one used during test (i.e., T0 = 418 K). In accordance with experimental conditions of initial rate (pure reactants in the feed) and holding the differential reactor conditions, the water contribution can be neglected in in all the models (PW = 0). Experimental data from Table S1 (Supporting Information) were used to estimate the parameters of the literature model (I to VI) by using a commercial software (CurveExpert Professional 2.0) for nonlinear regression. Data are reported in Table 4, also including the correlation coefficient r2. Model III, IV, and V did not succeed in fitting the experimental data and therefore Table 4 does not include the relative kinetic parameters. It is noteworthy that for any effective model, a positive value of methanol adsorption heat was found, apparently in contrast with the Langmuir− Hinshelwood theory. This situation can be explained considering that the adsorbed methanol is a reactive species, and its interaction with the catalyst surface (affecting the adsorption heat) can be affected by the progress of the reaction. Therefore, even though a physical process of adsorption takes place, a contemporary surface reaction may affect the kinetic parameter estimation. 3.5. Complete Model: Water Effect and “Best Fit” Model. To complete the kinetic model, accounting also for the water effect, the isothermal curves of methanol conversion as

Figure 2. Methanol to DME conversion as a function of temperature in integral PBR. Lines are an eye-guide for the reader.

function of temperature. Since the slope of the conversion curves versus temperature approximates the local reaction rate, a linear behavior can be seen at low conversion, indicating a constant reaction rate (differential approach) in a wide range of operating conditions. On the contrary, when the methanol conversion increases, the effect of water becomes significant and the reaction rate decreases as indicated by the reduction of the curves slope. 3.4. Kinetic Analysis on Differential Reactor. Different models have been proposed in the open literature to fit methanol to DME conversion data, even though kinetic analyses were mostly performed on alumina-type catalysts. Table 3 summarizes the published kinetic models, all based on the well-know approach of Langmuir−Hinshelwood reaction mechanism. It is worth noticing that the effect of DME is neglected in all the proposed models, and only the dependence upon methanol and water partial pressure (PM and PW, respectively) is considered. In addition to these models (from I to VI) a new proposed model (VII) is also included in the table, and it will be explained in detail in section 3.3. All the models include a kinetic constant k, depending upon temperature through to an Arrhenius-type model: D

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Table 4. Kinetic Parameters for Literature Modelsa

a

model

Eak [J/g mol]

k0 [mol/(gcat h)]

KM(T0) [bar−1]

ΔHads,M [J/(g mol)]

r2 [-]

I II III IV V VI

34000 ± 2000 9600 ± 3700 n.a. n.a. n.a. 48200 ± 1900

642 ± 312 83.7 ± 83.1 n.a. n.a. n.a. 6.5 × 106 ± 1.3 × 106 [mol/(gcat h bar)]

8.17 ± 0.17 0.95 ± 0.05 n.a. n.a. n.a. 2.56 ± 0.08

19700 ± 1000 4100 ± 2200 n.a. n.a. n.a. 48700 ± 1300

0.992 0.988

0.988

Notation: n.a. = not applicable.

reported in Figure 2 were considered. To estimate the remaining parameters KW,0 and ΔHads,W for each model, the Levemberg−Marquardt algorithm was used to compare experimental data of methanol conversion with the numerical values from the integration of eq 4 by considering the numerical values of kinetic parameters already shown in Table 4. The best-fit set of parameters (KW,0 ΔHads,W) was determined, as result of the minimization of the objective function, sum of the square of residuals, R = Σ(xM,calc − xM,exp)2 and the values are listed in Table 5, together with the correlation coefficient r2. Table 5. Water Adsorption Parameters for Literature Modelsa

a

model

KW(T0) [bar−1]

ΔHads,W [J/(g mol)]

r2 [-]

I II VI

91 ± 16 n.a. 70 ± 12

−9500 ± 2400 n.a. −4200 ± 2300

0.986

Figure 3. Comparison between calculated and experimental data of Model I28 (closed symbols from eq 4 integration).

0.988

Notation: n.a. = not applicable.

is proposed. Also in this case, according to the other kinetic equations, the effect of DME adsorption was neglected:

Also in this case one of the residual models (II) failed to converge in the optimization procedure, therefore no values for kinetic parameters are reported. To evaluate what is the best fitting model the statistical analysis of section 2.4 was performed between the two models, I and VI, separately for data from integral and differential reactors, as shown in Table 6.

−rM,0 =

QI−VI

integral reactor data [FC = 2.22]

0.64

0.95

(8)

where k1 is the surface reaction kinetic constant, depending upon temperature via an Arrhenius-type model: ⎡ Ea,1 ⎤ k1(T ) = k1,0 exp⎢ − ⎥ ⎣ RT ⎦

Table 6. Statistical Comparison of Kinetic Models I and VI differential reactor data [FC = 1.98]

n k1PM [1 + k 2(PM)q + k 3(PW )s ]m

(9)

where k1,0 is the pre-exponential factor and Ea,1 the activation energy of the surface reaction. In addition, k2 and k3 are the adsorption constants of methanol and water, respectively, depending upon temperature according to a Van’t Hoff-type model as follows:

The parameter QI−VI exhibits a value lower than the Fisher’s distribution for either differential or integral reactors data and, as consequence, the model I, proposed by Gates & Johanson28 can be identified as the most effective in interpolating experimental data in the entire methanol conversion range. A plot comparing experimental and calculated methanol conversion data, reported in Figure 3 exhibits a maximum error of 14%. It is also important to notice that the calculated values of activation energy are in good agreement with previous literature findings.25 In addition, the activation energy calculated by model I on γ-Al2O3 was found23 to be about 113 kJ/g mol. This value is sensibly higher than that reported in Table 4, confirming the MFI as more active than alumina in the investigated reaction. 3.6. Proposed Model. The models tested so far have been developed mainly for alumina catalyst; therefore, starting from a generic saturation equation, a new model developed for H-MFI

⎡ Ea, i ⎛ T0 ⎞⎤ ⎜ ki(T ) = ki ,0 exp⎢ − − 1⎟⎥ ⎝ ⎠⎦ ⎣ RT0 T

(10)

where the reference temperature T0 was fixed at 418 K, ki,0 is the adsorption constant at the reference temperature T0 and Ea,i is the activation energy of the adsorption processes of methanol (i = 2) and water (i = 3). The value of the exponents in eq 8 depends on the assumed mechanism and it can be fixed according to the following hypothesis: the parameter n is related to the number of methanol molecules involved in the reaction, n = 2, from stoichiometry. The parameter m is related to the number of sites involved in the reaction and, according to some literature work,20 it is assumed that any methanol molecule interacts with two sites. Therefore, for two molecules of methanol involved in the reaction, four sites are involved determining m = 4. The assumption is that the interaction E

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4. CONCLUSIONS This paper is focused on the kinetic analysis of methanol dehydration to DME catalyzed by H-MFI zeolite. This zeolite can effectively replace the alumina as acid catalyst for alcohol dehydration, ensuring a better stability versus water. Despite the promising results in a catalytic test, no kinetic analysis was performed on this zeolite. For this reason, aiming to partially cover this topic, the present work presented a kinetic analysis of methanol dehydration over MFI catalyst, testing the models already developed for alumina in the same reaction. Both differential or integral approaches were followed, in order to develop a complete model. On the basis of the Fisher’s distribution test comparison, it was found that, among the literature models, the well-known model of Gates and Johanson28 was the best in fitting experimental data, and water adsorption heat was in agreement with previous literature work. In addition a new fitting model was proposed, and the related parameters were calculated as a function of temperature. The proposed model was based on a different kinetic mechanism leading to a different set of numerical values for the exponents of the kinetic parameters. The model was tested using the experimental data, and the adsorption heat for water was found to be in good agreement with expectations. In addition the application of the Fishers’ distribution test showed that the proposed model achieved a better fitting performance with respect to the best model already published. Finally, the kinetic parameters for methanol dehydration on H-MFI were calculated and a new kinetic model was also proposed with an aim to improve the fitting of experimental data obtained from a catalyst never investigated in terms of kinetic analysis.

between the reactant and the adsorption sites takes place with different features: one proton interaction and one via physical adsorption. This indicates that, for each acid site on the zeolite surface, there is a f ree site for physical adsorption, and that methanol is adsorbed on the surface also when interacting with the acidic site. In addition, it is assumed that the parameter q is related to the number of acid sites involved in the reaction for a unit of product molecule, therefore q = 2. The last parameter is s, related to the number of sites needed for the water adsorption, hence s = 1. The final form of the proposed model is reported in Table 3 (model VII) and it is worth noticing that the assumptions still allow one to consider k3 as the adsorption constant of water. The kinetic parameters for model VII were calculated in the same way as for literature models and data are summarized in Table 7, either for differential or integral reactor data, with the related correlation coefficient. Table 7. Kinetic Parameters for Model VII k1,0 [mol/(gcat h bar2)] Ea,1 [J/(g mol)] k2,0 [bar−2] Ea,2 [J/(g mol)] k3,0 [bar−1)] Ea,3 [J/(g mol)]

9.55 × 107 ± 3.7 × 106 62300 ± 100 22.52 ± 0.7 13500 ± 1500 43 ± 6.2 −22100 ± 1600

r2 = 0.998

r2 = 0.990

In addition, to evaluate the model prediction with respect to the literature models, a statistical comparison was performed between the best model of the set (model I) and the proposed equation. It was confirmed by statistical analysis (Table 8) that



Table 8. Statistical Comparison of Kinetic Models I and VII

QVII‑1

differential reactor data [FC = 1.98]

integral reactor data [FC = 2.22]

0.32

0.84

ASSOCIATED CONTENT

S Supporting Information *

Experimental conditions and kinetic data for initial rate tests are listed in Table S1. Figure S1 shows the catalyst nitrogen adsorption isotherm at 77 K. This material is available free of charge via the Internet at http://pubs.acs.org.

the proposed model is the best fitting equation for methanol conversion over H-MFI in the investigated temperature range. In Figure 4 the plot of experimental versus calculated conversions are shown (maximum error of 11%). In the case of the proposed model, the adsorption heat of water is in good agreement with open literature data, even though available values refer to a Na−H−MFI (Na/Al ratio = 0.4).25



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel.: +390984496641. Fax: +390984496655. Notes

The authors declare no competing financial interest.



REFERENCES

(1) Semelsberger, T. A.; Borup, R. L.; Greene, H. L. Dimethyl ether (DME) as an alternative fuel. J. Power Sources 2006, 156, 497−511. (2) Arcoumanis, C.; Bae, C.; Crookes, R.; Kinoshita, E. The potential of di-methy ether (DME) as an alternative fuel for compressionignition engines: A review. Fuel 2008, 87, 1014−1030. (3) Ogawa, T.; Inoue, N.; Shikada, T.; Ohno, Y. Direct dimethyl ether synthesis. J. Nat. Gas Chem. 2003, 12, 219−227. (4) Cheng, C.; Zhang, H.; Ying, W.; Fang, D. Intrinsic kinetics of one-step dimethyl ether synthesis from hydrogen-rich synthesis gas over bi-functional catalyst. Korean J. Chem. Eng. 2011, 28, 1511−1517. (5) Hu, J.; Wang, Y.; Cao, C.; Elliott, D. C.; Stevens, D. J.; White, J. F. Conversion of biomass syngas to DME using a microchannel reactor. Ind. Eng. Chem. Res. 2005, 44, 1722−1727. (6) Bonura, G.; Cordaro, M.; Spadaro, L.; Cannilla, C.; Arena, F.; Frusteri, F. Hybrid Cu-ZnO-ZrO2/H-ZSM5 system for the direct synthesis of DME by CO2 hydrogenation. Appl. Catal., B 2013, 140− 141, 16−24.

Figure 4. Comparison of data from model VII and experimental data. F

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dx.doi.org/10.1021/ie502775u | Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX