Deactivation Kinetics for Carbonylation of Dimethyl Ether to Methyl

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Deactivation Kinetics for Carbonylation of Dimethyl Ether to Methyl Acetate on H-MOR Zaizhe Cheng, Shouying Huang, Ying Li, Jing Lv, Kai Cai, and Xinbin Ma Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.7b03500 • Publication Date (Web): 23 Oct 2017 Downloaded from http://pubs.acs.org on November 1, 2017

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Industrial & Engineering Chemistry Research

Deactivation Kinetics for Carbonylation of Dimethyl Ether to Methyl Acetate on H-MOR Zaizhe Cheng, Shouying Huang*, Ying Li, Jing Lv, Kai Cai, Xinbin Ma* Key Laboratory for Green Chemical Technology of Ministry of Education, Collaborative Innovation Centre of Chemical Science and Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 30072, P R China.

E-mail: [email protected]; [email protected] Key Words: carbonylation, dimethyl ether, mordenite, deactivation, kinetics

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ABSTRACT: The carbonylation of dimethyl ether (DME) to methyl acetate (MA) is one of the crucial step in an indirect synthesis route of ethanol from syngas (CO+H2). H-MOR zeolite exhibits excellent activity and selectivity at mild conditions. However, the catalyst suffers rapid deactivation due to the carbonaceous deposits on Brønsted acid sites. In this study, the deactivation kinetics for the carbonylation of DME to MA on H-MOR zeolite was investigated. Based on the fitting results and in situ FTIR analysis, a model taking into account the composition concentration was established. This deactivation kinetic model allows simulating concentration of different compounds in reaction medium with time on stream under different experimental conditions. In this model, coke is considered to be derived from DME and CO. Moreover, CO remarkably accelerates the coke formation and the effect of its concentration on deactivation rate is quantified. The establishment of deactivation kinetics will be conductive to elucidate coke formation mechanism and optimize the process conditions.

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1. INTRODUCTION Ethanol, as one of the most important fuel additives or alternatives, is regarded to be able to alleviate the concern for the security of petroleum supply.1 With high evaporation heat and octane number, ethanol can be blended with gasoline or diesel in automotive engine.2 In addition, it can also be used as solvent and feedstock in chemical industry.3,4 Nowadays, the traditional processes for ethanol production are hydration of ethylene5 and fermentation of biomass.2,6 Recently, several synthetic processes of ethanol from syngas have attracted worldwide interest. Among them, a novel process has received much attention, which is an integrated technology consisting of carbonylation of

dimethyl ether (DME) to methyl acetate (MA) and hydrogenation of MA to ethanol (Eqs. (1)-(2)). The reactants, syngas can be derived from gasification of coal or biomass as well as reforming of nature gas,6,7 which is widely sourced with low cost. Besides, this process exhibits high atom economy (the obtained methanol can be circulated to produce DME), mild operation conditions and few emission, making it a promising and competitive route in industry.8

CH3OCH3 + CO → CH3COOCH3

(1)

CH3COOCH3 +2H2 → C2H5OH+CH3OH

(2)

Carbonylation of DME to MA is a key reaction in this process. Fujimoto9 first demonstrated aluminosilicate zeolite could catalyze carbonylation of methanol in the absence of halogen promoter. However, H2O, resulting from dehydration of methanol, suppresses the reaction because of competitive adsorption with methyl group. Iglesia and his co-workers10,11 studied the carbonylation of DME on different zeolites (e.g. H-MOR, H-FER and H-MFI) and proposed it is a specific shape-selective reaction. H-MOR zeolite consists of the main 12-membered ring (12-MR) pores (0.67 3



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×0.7 nm), a parallel compressed 8-membered ring (8-MR) pores (0.28×0.57 nm) and an 8-MR pores (0.34×0.48 nm) vertically connected to the main 12-MR channels. Due to the confinement effect of 8-MR channels, H-MOR catalyst exhibits excellent initial activity and selectivity. Nevertheless, coke can be easily deposited on acid sites in 12-MR channel because of the larger spatial size, which leads to the rapid deactivation. This has become the main restriction in industrialization of the technology. To date, studies12-17 on carbonylation of DME to MA mainly aim at improving the activity of catalyst, while few papers13,18 focus on the deactivation mechanism. To our knowledge, there is no work concerning the deactivation kinetic modeling of this reaction in the published work. The detrimental formation of coke is always one of the factors limiting the application of zeolite materials. The deactivation kinetic study is not only conducive to elucidate the deactivation mechanism but also important for the design of the reactor. In some similar reactions, such as methanol to olefins (MTO) and methanol to gasoline (MTG) process, coking has long been studied including the discussion about deactivation modeling.19-21 Sedran et al.22 proposed a deactivation kinetic model of methanol to hydrocarbon process, without taking into account the composition concentration. This model is empirical and simplified. Benito et al.23 developed a deactivation kinetic model considering reactants and products concentrations, which is proved to be suitable in a wide range of experimental conditions. In this article, several deactivation kinetic models were proposed considering the component concentration in the reaction medium, and a rigorous methodology24 was carried out in this study to calculate the deactivation kinetic parameters and distinguish the hypothetic models. Moreover, FTIR analysis was employed to establish the most suitable model based on coke formation mechanism. 4


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2. EXPERIMENTAL SECTION 2.1. Catalyst Preparation and Parameters. Reagents include sodium hydroxide, sodium aluminate, 25 wt.% tetraethylammonium hydroxide solution (Tianjin Guangfu Fine Chemical Co., Ltd.), silica sol (30 wt.% SiO2, Qingdao Zhuorongyuan silicon products Co., Ltd.), NH4NO3 (≥ 99%, Standard Technology Company, Tianjin, China) and nitrogen, argon, dimethyl ether, carbon monoxide, helium (high purity, Tianjin Sixon Gas Co.,Ltd). The Na-MOR catalyst was prepared by hydrothermal method with sodium hydroxide, silica sol, sodium aluminate and tetraethylammonium hydroxide solution as described in our previous work. 25

After stirring the mixture for 1 h, the gel was transferred into a Teflon autoclave for

hydrothermal crystallization at 443 K for 72 h. Then the Na-MOR catalyst was obtained by filtration, washing with distilled water, drying overnight and calcination at 823 K for 5 h to remove the organic template. Afterward, the Na-MOR catalyst was stirred in NH4NO3 aqueous solution (0.5 mol/L) at 353 K for 6 h twice to remove Na+ ions. Followed by washing with distilled water, the samples were dried at 383 K overnight and calcined at 823 K for 4 h with a heating rate of 1 K/min to get H-MOR catalyst. Then the catalyst was compacted, crushed and sieved to obtain 0.250-0.425 mm particles. The physical properties of H-MOR zeolite, determined by N2 adsorption-desorption (Micromeritics, ASAP 2020), are as follows: BET surface area, 438 m2 g-1; micropore area, 418 m2 g-1; total pore volume, 0.234 cm3 g-1; micropore volume, 0.195 cm3 g-1. The total acidity is 1.02 mmol g-1, measured by NH3-TPD characterization performed on Micromeritics Autochem II 2920 apparatus. In addition, the details of the measurements are described in the Supporting Information. 5



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2.2. Equipment and Reaction Conditions. The kinetics evaluation was carried out on an automated appliance (Figure 1) equipped with an isothermal fixed-bed reactor, of which was stainless steel with 8 mm internal diameter. A constant temperature zone of 10 cm was provided by means of three temperature controllers, and reaction temperature was monitored by another thermocouple in the middle of catalyst bed. All the products were analyzed on-line by an Agilent 7890B gas chromatograph, which was equipped with a flame ionization detector (FID) and a thermal conductivity detector (TCD). Four columns were used: (1) a PoraPLOT Q column for separating DME, MA, methanol, acetic acid which are detected by the FID; (2) two Porapak Q and a MolSieve 5A columns for separation of Ar, N2, hydrocarbons and CO components that were detected by the TCD. The detected byproducts are only methanol and acetic acid, and DME conversion and MA selectivity can be calculated by Eqs (3) and (4), respectively.

X DME =(CDME,inlet -CDME,outlet )/CDME,inlet

(3)

SMA =MA/(CH3OH/2+MA+CH3COOH)

(4)

After purging by Ar under 473 K for 9 h to remove the adsorbed water in catalyst, the reaction experiments were carried out by feeding DME and CO under the conditions listed in Table S1.

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Figure 1. Schematics of reaction system. Equipment, D-01 N2/DME/CO cylinder, D-02 Ar cylinder, R-01 fixed bed reactor, PCV-03 backpressure valve, MFC mass flow controller, PI, pressure indicator, TIC, temperature sensor and controller, TI, temperature sensor. 2.3. In situ FTIR Analysis. In situ FTIR spectra were acquired on a Nicolet 6700 instrument equipped with a MCT detector. The powder of H-MOR catalyst was pressed into self-supported wafer (about 16 mg) and placed into an in-situ FTIR cell with ZnSe windows. Each spectrum was recorded in the range of 650-4000 cm-1 with a resolution of 4 cm-1 at 483 K. The effect of CO concentration on the formation of carbonaceous deposits was investigated by analyzing the “coke region” (1350-1750 cm-1) in FTIR spectra.26-28 Prior to adsorption of reactants, the sample was heated in He (20 mL/min) at 823 K for 1 h to clean the surface of catalyst and subsequently, cooled down to 483 K. The pretreated catalyst was exposed to 10 % DME/N2 (mL/min) for 20 min, followed by purging He for 30 min to remove gaseous and weak absorbed DME. Then CO/He gas mixtures (50 mL/min) with different concentration were introduced into the in situ cell. The spectra was obtained continuously during the process, thus evolution of coke formation with time 7



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could be monitored.

3. RESULTS AND DISCUSSION 3.1. Deactivation Behavior. Despite of the high initial reaction rate on H-MOR catalyst, the catalyst suffered a rapid deactivation, mainly due to the coke deposits on acid sites. We investigate the influence of different experimental conditions, such as reaction temperature, pressure and space time. As depicted in Figure 2, the results of DME conversion and MA selectivity on H-MOR under different temperature, W/FDME and pressure are plotted as a function of time on stream, which are presented in Figure 2 (a-b), (c-d) and (e-f), respectively. Besides, more results under other experimental conditions are described in Figure S1. As shown in Figure 2(a), (c) and (e), there is an obvious induction period in this reaction. During this period, DME absorbs on Brønsted acid sites and transforms into methoxy species. At the same time, methanol is detected in the off-gas, while few MA is generated via the reaction of CO with methoxy species. This period was also reported by Cheung et.al,10 they found that the formation rate of MA increased with time. On the contrary, the methanol rate decreased. Once the active sites are saturated with methoxy species, the methanol generation ceases and the yield of MA achieves to the maximum. Moreover, it is apparently observed in Figure 2(c) that a low space time will be in favor of shortening the induction period. After the induction period, the conversion of DME reaches the maximum value and then decreases with time on stream, indicating the gradual deterioration of catalysts in the reaction. In Figure 2 (a), the conversion of DME presents a more rapid reduction at the higher temperature (483 K), because the coke formation is facilitated under the higher temperature.29 Therefore, reaction 8


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temperature has a significant impact on the deactivation rate. On the other hand, the conversion of DME also declines with the decrease of space time. Regarding the effect of space time on deactivation, some researchers30 suggested that deactivation of catalyst was more pronounced with the increasing space time. However, the deactivation rate does not show a clear correlation with space time in our reaction. Moreover, we found that the higher pressure will accelerate the carbonylation reaction, while the deactivation becomes more severe meanwhile. In addition, the selectivity of MA in Figure 2(b) (d) and (f) maintains above 95%. At elevated temperature (e.g. 483 K), more methanol was generated (Figure S2) with the reducing concentration of MA during the deactivation. Therefore, the selectivity slightly decreased, which could be observed in Figure 2(b).

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Figure 2. The DME conversion (left) and MA selectivity (right) on H-MOR catalyst versus time on stream under different temperatures (a-b), space time (c-d) and pressures (e-f), DME/N2/CO=2/5/93.

3.2. Kinetics of Carbonylation of DME to MA. Due to the excellent selectivity of H-MOR catalyst on carbonylation of DME to MA reaction (nearly 100%), the components in the reaction medium are mainly three species: (i) DME, the primary reactant, forms methoxy species on Brønsted acid sites of zeolites.31 (ii) CO, which is reactant and in the majority of the reaction system, (iii) MA, the principal product in this reaction. The kinetic studies were carried out to elucidate the effect of DME and CO pressure on MA synthesis rate. As shown in Figure 3 (a), when DME pressure is increased with the constant CO pressure, the MA space time yield (STY) remains invariant, unaffected by DME pressure. While the MA STY increases linearly with CO pressure in Figure 3(b), suggesting that the CO pressure has a significant effect on MA synthesis rate. Therefore, the carbonylation rate depends on DME and CO pressures kinetically with zero- and first-order, respectively, which is in line with Cheung’s work. And the kinetics equations of different components in the reaction medium can be denoted as follows: rMA =

dyMA = kfCO d (W / FDME )

(3) 10


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rDME =

dyDME = −kfCO d (W / FDME )

rCO =

dyCO = −kfCO d (W / FDME )

(4) (5)

where fCO is the fugacity of CO , W/FDME is the contact time and ri is the reaction rate of each component.

Figure 3. Effect of (a) DME and (b) CO pressure on the MA STY, 478 K. The data for the initial reaction rate are collected at the highest conversion of DME to exclude the effect of deactivation, rather than in the induction period. And the kinetic parameters in each equation proposed above are calculated by minimizing an error objective function, Ф, which is defined as the sum of square relative errors between experimental and calculated component values:

 yi* − yi  Φ = ∑φi = ∑   yi  i =1 i =1  nv

nv

2

(6)

where Øi demotes square relative errors for each compound, nv is the number of the components in the kinetics equations to be fitted, yi is experimental molar fraction for component i, and y*i is the corresponding calculated molar fraction for component i. In order to reduce the correlation between the frequency factor and activation energy, which are related to Arrhenius equation, we parameterize the kinetics parameters as follows:

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k = k * exp[−

E 1 1 ( − )] R T T*

(7)

Accordingly, the calculated kinetic parameters are constant at the reference temperature (T*=473 K) and corresponding activation energy, E. A program involving experimental data and reaction conditions was carried out by using MATLAB to calculate the kinetic parameters. More specifically, the code sequentially used a forth-order Runge-Kutta method to integrate the ordinary differential equations and minimize the objective function by multivariable nonlinear regression. The calculated values of the kinetic parameters are: k= (1.792±0.206) gDME (gcat)-1 h-1 (kPa)-1 and activation energy E = 88.65±0.93 kJ mol-1, at the reference temperature 473 K.

Figure 4. Comparison of experimental (points) and calculated results (lines) for compound concentration as a function of contact time at different temperature: (a) 468 K (b) 473 K. Reaction conditions: pressure, 1.5 MPa; DME/N2/CO=2/5/93. Figure 4 illustrates the comparison of experimental and calculated results for the concentration of DME, CO and MA as a function of contact time. The concentration of each component, yi, is defined as the molar fraction of each compound in the reaction medium. When space time is increased, the 12


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content of DME and CO are gradually decreased. It indicates that the longer contact time leads to a higher conversion of DME. Compared with Figure 4(a), a remarkable increase of MA is observed in Figure 4(b) due to elevated reaction temperature. Additionally, the total concentration value of DME, CO, MA and N2 approximate 100% under different experimental conditions, reflecting the extremely high selectivity of MA in this reaction. The good fit of experimental results with the kinetic Eqs. (3)-(5) indicates the rate of carbonylation reaction solely depends on CO concentration, which is consistent with the observation of Cheung et al.’s work.32 The initial reaction rate on the fresh catalyst at different experiment conditions is figured out in this part, which can be used to calculate the deactivation kinetic parameters in the deactivation period.

3.3. Proposed Deactivation Kinetic Models. It has been established20,23 that it is necessary to adopt a composition-dependent kinetic model for simulation of catalyst deactivation in a fixed-bed integral reactor, because the composition concentration exerts an important influence on coke formation. In the system of methanol to olefins (MTO), oxygenates (e.g. methanol and DME), light olefins and other products (mainly including paraffins and aromatics) are considered as the coke precursor species,19,33 whose concentrations are involved in the proposed deactivation kinetic model equations. In dehydration of glycerol reaction, glycerol and products are supposed as possible coke precursors, whose concentrations are also included in the proposed models.

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Based on the previous

studies in carbonylation of DME to MA, carbonaceous deposition has been proved as the main reason of the catalyst deactivation, which occurs on acid sites.29 The general deactivation kinetic model considering the individual contribution of coke precursors can be defined as follows:

13



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-

da = ∑ kdi yi a d dt i

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(8)

where yi is the molar fraction of each component, kdi is the kinetic constant for deactivation by coke of each component, and d is the order for deactivation, a, the relative catalyst activity, is the ratio of the formation rate at t time to the initial rate without coke:

a=

rMA ( rMA )0

(9)

(rMA)0 can be figured out with the kinetic parameters in Table 1. The species in the reaction medium detected by GC are mainly DME, CO and MA, which are possible coke precursors. The establishment of coke precursors depends on the mechanism of coke formation. However, it has not been clarified until now in this reaction system. For MTO reaction, oxygenates (methanol and DME) are considered as possible coke precursors, which convert to ethylene by dehydration on acidic zeolite followed by hydrocarbons formation through oligomerization-cracking35 or hydrocarbon pool mechanism.36,37 In consideration of the similarities of these two reactions, such as similar reactants (DME and methanol), reaction temperature (above 473 K) and active sites (Brønsted acid sites in aluminosilicate zeolite), we propose DME as one of the possible coke precursors. On the other hand, it hasn’t been established if CO contribute to the formation of coke. Therefore, the role of CO is also taken into account in the following investigation. Given the uncertain role of different species in the medium for coke formation, several different assumptive kinetic equations for deactivation are proposed in Table 1: (i) Model 1 considers that deactivation rate is independent of any reaction medium concentration. (ii) Model 2 assumes a deactivation kinetics that is dependent on the DME concentration, considering DME as the sole coke 14


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precursor. (iii) Model 3 considers CO as coke precursor, and the deactivation rate is dominantly dependent on CO. (iv) Model 4 considers that coke formation is related to DME concentration as well as CO, both of which transform into coke intermediates parallelly. (v) Model 5 also considers that both DME and CO are coke precursors, while, different from Model 4, DME and CO generate coke intermediates in a consecutive reaction. Table 1. Kinetic equations proposed for the deactivation Model

Kinetic equation

1

-

da =k y ad dt d DME

2

-

3

-

4

-

5

da =k ad dt d

da =k y ad dt d CO

da =k (y +y )ad dt d DME CO -

da =k y y ad dt d DME CO

3.4. Methodology for Deactivation Kinetics. A methodology is carried out to simulate the concentration of different components with time on stream. The methodology is based on the kinetic Eq. (3)-(5) and the proposed hypothetic deactivation equations, which contains different experimental parameters (reaction temperature, components concentration, time on stream). Then the most suitable model is established according to the fitting quality and significance test. The formation rate of MA at t time on stream can be defined as follows:

rMA = kfCO a

(10)

The kinetic constants for deactivation kinetic model are obtained by minimizing an error

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objective function, in which Ф is defined as the sum of square relative errors between experimental and calculated component concentration values:38 2

 y* − yi  Φ = ∑∑φi = ∑ i  yi  i =1 j =1 i =1  nv nexp

nv

(11)

where Øi is square relative errors for each compound, nv is the number of the components in the kinetics equations, nexp is the number of experiment, yi is experimental molar fraction for component i, and y*i is the corresponding calculated molar fraction for i. Iglesia et al. found the rate of MA synthesis was proportional to CO pressure. Since then, a high ratio of CO to DME (50:1 ~10:1) is commonly adopted in carbonylation of DME.10 In this study, owing to the great discrepancy in the concentration of different components (CO accounts for above 92%), the arithmetic square residual is not appropriate to reflect the deviation accurately and intuitively. Thus, we employ the relative square residuals in Eq. (11) to reveal the degree of deviation between the calculated and experimental points for each proposed deactivation kinetic model. A program involving deactivation kinetic models, experimental data and reaction conditions is conducted by MATLAB to calculate the deactivation kinetic parameters. Unlike the code in calculation of carbonylation reaction, the code for deactivation kinetic simulation includes some extra factors, such as time on stream and composition concentration. This simulation bases on an algorithm using multivariable nonlinear regression to acquire the optimal parameters of different proposed models. Discrimination of different deactivation kinetic models is achieved by the value of F (Fisher test of significance). We compare the ratio of residual variance (σ2) of different models with the critical 16


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statistical value Fα (α=0.05) to evaluate the significance.39 Thus, when Model i fits much better than Model j, the ratio of residual variance of the two models will conform to:

(σ ) (σ )

2 f i 2 f j

>Fα ( ν f )i , ( ν f ) j   

（12）

3.5. Kinetic Parameters. The results of kinetic parameters with a 95% confidence interval are exhibited in Table 2, as well as the error objective function corresponding to each optimal fitted deactivation kinetic model. By comparing the Φ values of different models, Model 1, corresponding to independent deactivation, shows the poorest coincidence with the experimental data. Model 5, simultaneously considering the concentration of DME and CO in the hypothetic kinetic equation, has the best prediction of deactivation behavior. Model 3 and 4 are more adequate than Model 1, but much worse than Model 5. It is noteworthy that Model 2 also has a good agreement with experimental data, very similar to Model 5. Different model stands for different coke formation mechanism. In Model 2, DME transforms into coke individually. In published work, DME can react with Brønsted acid sites to form methoxy species, then ethylene is generated by the dehydration reaction.36 Furthermore, hydrocarbons are formed through oligomerization-cracking or hydrocarbon pool mechanism from olefins. Similarly, CO is taken into account in Model 3 as the only coke precursor to generate coke. In our FTIR experiments, when CO was injected into the reaction cell, no characteristic adsorption peaks of CO or hydrocarbons were observed, thus coke could not be formed only in presence of CO. This result is in consistent with the poor fitting results of Model 3. In Model 4, DME and CO generate coke parallelly, which is also not reasonable from the fitting results. Different from Model 4, in Model 5 coke is formed from DME and CO in kind of consecutive reaction. Table 3 shows the significance test 17



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results for the comparison of Model 5 with other Models. Also, it is evident that Model 5 is significantly better than Model 1, 3 and 4, but it’s difficult to distinguish which one is better between Model 2 and 5. In view of the dominated content of CO in the reaction system, the slight superiority of Model 5 in error object function may be attributed to the nearly constant CO concentration with time on stream. Consequently, we cannot confirm the effect of CO in deactivation only by kinetic investigation, which will be explored in the following section. Table 2. Kinetic parameters for the proposed deactivation kinetic equations Parametersa

Model 1

Model 2

Model 3

Model 4

Model 5

K*d , h-1

0.164±0.015

12.95±0.944

0.177±0.016

0.174±0.016

13.97±1.018

d*

1.381±0.268

1.321±0.199

1.377±0.267

1.370±0.265

1.323±0.199

Ed, kJ mol-1

109.43±15.85

158.33±24.45

109.54±15.52

108.70±15.77

158.50±27.30

Ф

1.8514

1.1813

1.8394

1.8177

1.1810

σ2

9.796 10-3

6.250 10-3

9.732 10-3

9.617 10-3

6.249 10-3

a

The superscript * indicates the value at 478 K.

18


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Table 3. Significance test results for Model 5 compared with Models 1-4 Parameters

Model 1

Model 2

Model 3

Model 4

(σ2f )i/(σ2f )5

1.568

1.000

1.557

1.539

(νf)i

189

189

189

189

F0.05[(νf)i,(νf)5]

1.271

1.271

1.271

1.271

Significant test

valid

not valid

valid

valid

3.6. Model Discrimination. Compared with catalytic activity measurements, FTIR analysis is extremely sensitive to monitor the evolution of species on the catalyst surface. In this work, we apply in-situ FTIR to elucidate the influence of CO on coke formation, as a complementary evidence for kinetic study. Figure 5 illustrates the evolution of spectra with time in the “coke region” (from 1350 cm-1 to 1750cm-1), when CO is introduced into the reaction cell after DME adsorption. The bands at 1596 cm-1 and 1496 cm-1 are the indicators for the presence of coke.26,40 The former is attributed to highly unsaturated polyenes or condensed aromatics species, and the other one is due to C=C bond of polyenes or non-condensed aromatics. Moreover, the weaker bands at 1388 cm-1 and 1368 cm-1 are assigned to C−H bending modes of paraffinic species, which are likely linked to aromatics.41 In this experiment, after removing the gaseous DME and weak adsorbed methoxy groups, the intensity of bands at 1596 cm-1 and 1496 cm-1 are at a low level. Once CO is introduced, a remarkable increase of these two bands is observed, indicative of the promotion effect of CO on coke

19



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formation. In other words, CO is of vital importance to the catalyst deactivation. Furthermore, experiments with different CO concentration are performed to provide an insight into the role of CO. By modulating the concentration of CO (20%, 40%, 60% and 100%), the intensity of the band at 1596 cm-1 is plotted with time on stream. The variation trend is presented in Figure 6, the correlation of coke formation rate with CO concentration can be denoted by a simplified equation: rcoke =k·ynCO, n=0.6 As the four experiments underwent the same DME adsorption procedure, k is an integration parameter of reaction rate constant and adsorbed DME concentration, it is obvious that the rate of coke formation is proportional to the CO concentration. The higher partial pressure of CO results in an acceleration of coke deposit. As mentioned above, the deactivation is due to the severe carbonaceous deposits in the zeolite channels, hence the deactivation rate should be associated with the CO concentration. Moreover, the growth momentum of deactivation rate slows down with increasing CO concentration. Therefore, due to the considerable proportion of CO (≥ 90%) in the reaction medium, the change of CO concentration is negligible with time on stream, resulting the unnoticeable difference of sum relative square residuals between Model 2 and Model 5. To summarize the results from both kinetic study and in-situ FTIR analysis, Model 5 is the most suitable prediction for the catalyst deactivation in DME carbonylation. To date, a few researchers have noticed the facilitating effect of CO on coke formation. In comparison of MTO or MTG process, carbonylation of DME to MA catalyzed by H-MOR suffers a severer deactivation even at lower reaction temperature (473 K). Liu et al.42 pronounced that a small amount of CO, derived from decomposition of methanol at 643 K, gives rise to the olefin products. 20


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Then, the intermediate species transform into carbonaceous deposit through polymerization and hydrogen transfer reactions. Thus, the process can be interpreted as a kind of consecutive reaction for Model 5. However, the mechanism how CO transforms into the coke intermediates is still not clarified, several researchers42,43 proposed the insertion of CO into absorbed methoxy species on Brønsted acid sites is a potential pathway of carbon-chain growth to generate coke intermediates, which should be studied further in future work. In carbonylation of DME, CO predominate in the reaction medium, so it reasonably explains why the deactivation behavior is aggravated even at a lower temperature.

Figure 5. Evolution of “coke region” bands of FTIR spectra after injection of CO.

Figure 6. Variation trend of the intensity of “coke region” bands with time after injection of CO with 21



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different concentration.

3.7. Model Verification. The established deactivation kinetic model allows simulating the composition concentration in the reaction medium as a function of time on stream. In order to examine the validity of Model 5, the comparisons of experimental data (points) with simulated results (lines) derived from Model 5 are presented in Figure 7-9, Figure S2 and S3, which have revealed a satisfactory fit of the experimental and calculated data.

Figure 7. Comparison of experimental (points) and calculated (lines) results for the compound concentration as a function of time on stream for different space time. Reaction conditions: temperature, 478 K; pressure, 1.5 MPa; DME/N2/CO=2/5/93.

Figure 8. Comparison of experimental (points) and calculated (lines) results for the compound concentration as a function of time on stream at different temperature. Reaction conditions: pressure,

22


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1.5 MPa; DME/N2/CO=2/5/93.

Figure 9. Comparison of experimental (points) and calculated (lines) results for the compound concentration as a function of time on stream at different pressure. Reaction conditions: temperature, 478 K; W/FDME=3.88gcath/gDME; DME/N2/CO=2/5/93.

4. CONCLUSION In carbonylaiton of DME to MA, H-MOR exhibits excellent initial conversion and nearly 100% selectivity but suffers a severe deactivation because of the carbonaceous deposit in the channel of zeolite. In this work, five model predictions depending on different deactivation mechanisms for deactivation behaviors were investigated and compared. The kinetic simulation took into account the concentration of component. Model 5 is proved the most suitable model for describing the 23



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deactivation process, introducing the fraction of DME and CO simultaneously that represents the influence of these two components on coke formation. As a supportive evidence, a complementary in-situ FTIR analysis demonstrates that CO remarkably accelerates the coke formation and its concentration has a remarkable impact on deactivation rate. This promotion effect explains the more rapid deterioration rate of DME carbonylation, when compared with MTO or MTG reaction, even at a lower reaction temperature. Moreover, the deactivation kinetic equation determined in this study allows predicting reagents and products distribution at different operating conditions and will contribute to the optimization of process conditions and the design of reactor.

ASSOCIATED CONTENT Supporting Information The details of N2 adsorption-desorption and NH3-TPD experiments, the kinetic experiments conditions (Table S1), the DME conversion and MA selectivity results on additional conditions (Figure S1), the MA and MeOH selectivity under different temperatures (Figure S2) and the comparison of experimental and calculated results on additional conditions (Figure S3 and S4).

AUTHOR INFORMATION Corresponding Authors *E-mail: [email protected] (Shouying Huang) *E-mail: [email protected] (Xinbin Ma) Notes The authors declare no competing financial interest.

ACKNOWLEDGMENTS 24


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Financial support from the National Natural Science Foundation of China (21325626, 21406120) and Postdoctoral Science Foundation of China (2015T80214) is gratefully acknowledged.

Notation a=activity, in Eq (9) d=the order for deactivation E=activation energy of the main reaction, kJ (mol)-1 Ed=activation energy of the deactivation kinetic model, kJ (mol)-1 FDME=mass flow rate of DME, g h-1 Fα=critical value of Fischer distribution for a 100(1-α) confidence level fCO=fugacity of CO, kPa k, k*=reaction rate constants of the main reaction and its value at reference temperature (473 K), (g of DME) h-1 (g of catalyst) (kPa)-1 kd, k*d =kinetic constant for deactivation and its value at reference temperature (478 K), h-1 nv = the number of the components in the kinetics equations nexp =the number of experiments R=universal gas constant, J (mol·K)-1 ri=formation rate of i component, (g of DME) h-1(g of catalyst) T, T*=temperature (K) and reference temperature (473 K) t=time on stream, h w=catalyst weight, g 25



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yi=vector of calculated molar fraction values for i component y*i = vector of calculated molar fraction values for i component

Greek letters α=confidence level Ф=sum of square relative errors, defined in Eq (6)

φi= square relative errors for each compound (σ2f )i= residual variance of Model i

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Table of Contents and Abstract Graphics

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Deactivation Kinetics for Carbonylation of Dimethyl Ether to Methyl

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