Ind. Eng. Chem. Res. 1992,31,497-502
497
Prediction of Product Distributions for Methanol Conversion to Hydrocarbons in a Pseudoadiabatic Reactor Ulises A. Sedran,t Frangois Sirnard,$Albert0 Ravella,$ and Hugo I. de Lasa*lt Chemical Reactor Engineering Centre, Department of Chemical and Biochemical Engineering, Faculty of Engineering Science, The University of Western Ontario, London, Ontario, Canada N6A 5B9, Instituto de Investigaciones en Catirlisis y Petroquimica (INCAPE) UNL-CONICET, Santiago del Estero 2654, (3000) Santa Fe, Argentina, and Research Laboratories, Esso Petroleum Canada, 453 Christina Street South, Sarnia, Ontario, Canada N7T 7Ml
A one-dimensional pseudohomogeneous model containing a new kinetic scheme for methanol conversion to hydrocarbons was used to simulate a pilot plant fixed-bed pseudoadiabatic catalytic reactor. A lumped-species kinetic model allowed the evaluation of product distributions under different experimental conditions, while experimentally measured temperature profiles along the reactor were followed closely. Furthermore, the kinetic parameters as calculated from the simulation were in agreement with those obtained in a kinetic study. Simulated concentration profiles inside the reactor showed the role of each kinetic lump and provided a basis for the selection of the operating conditions required to obtain desired product distributions.
Introduction The methanol conversion to hydrocarbons on ZSM-5 type zeolites is a reaction which has been studied extensively in both its fundamental and technological aspects (Chang, 1983). There is, at present time, an industrialscale process in New Zealand (Maiden, 1988) converting natural gas to gmlinerange hydrocarbons by applying the MTG Mobil process in adiabatic fixed-bedreactors. Other technological alternatives for the same process, like fluidized beds (Avidan and Edwards, 1986) and pseudoadiabatic operation of fmed beds (PO) (Ravella et al., 1987), have also been investigated. The pseudoadiabatic operation of a reactor provides an always increasing temperature profile along the longitudinal axis in a cocurrently cooled packed-bed catalytic heat exchanger/reactor (Soria-Lopez et al., 1981; de Lasa et al., 1986; Ravella and de Lasa, 1987). This design brings about considerable advantages with respect to other receptor configurations. For example, the hot spot location at the reactor exit, characteristic of the pseudoadiabaticoperation regime, facilitates operation and process control (de Lasa, 1987, 1989; de Lasa et al., 1989). The concept of pseudoadiabatic operation has also been tested in industrial units by Nikolov and Anastasov (1989), and the low parametric sensitivity of this type of reactor has been claimed by Borio et al. (1989). The successful measurement and modeling of the temperature profiles in a pilobplant unit converting methanol to hydrocarbons had been reported by Ravella et al. (1989). Moreover, the compatibility of PO with high methanol conversions and good selectivities was also confirmed (Ravella et al., 1989). In that study discrepancies between the predicted and experimental values for methanol conversion were mainly assigned to the noncomplete reliability of the kinetic expression used. There are few published kinetic descriptions for the catalytic conversion of methanol to hydrocarbons that could be applied to the reactor design and simulation considered in the present study (Chang, 1983; Sedran et al., 1990a). The complexity of the reacting system has generally imposed treatments which are based on the ~~
~~
~~
* To whom correspondence should be addressed.
+ Lnstituto de Investigaciones en Cattilisis y Petroquhica (INCAPE) UNL-CONICET. * The University of Western Ontario. Esso Petroleum Canada.
*
lumping of kinetic species in order to obtain tractable models (Sedran et al., 1990a). A model which describes methanol conversion to hydrocarbons as a function of six lumped kinetic species and which has been shown to be applicable in a wide range of temperatures, residence times, and catalyst deactivation degrees was recently developed using experimental data from a Berty reactor (Sedran et al., 1990b). In the present study, further testing and analysis of this kinetic model as applied to the simulation of a pilot-plant pseudoadiabaticunit converting methanol to hydrocarbons is presented. Other objectives of this research involve the prediction of product distributions and ita comparison with the experimental results and the simulation of temperature profiles, which define the pseudoadiabatic operation regime.
Experimental Section The characteristics of the pilot-plant unit designed on the basis of pseudoadiabaticoperation have been described elsewhere (Ravella and de Lasa, 1987; Ravella et al., 1987). The reactor consisted of a 2-m long, 3/4-in.schedule 40 pipe in AIS1 304 stainless steel, which was jacketed with an 11/4-in.schedule 40 pipe of the same material. The gap between the pipes allows the circulation of the cooling fluid (Monsanto Therminol75). Triads of thermocouples located in 10 positions along the reactor allowed the monitoring of temperature profiles, both radially and axially. Runs were performed with a catalyst containing zeolite ZSM-5 synthesized in our laboratories according to the methodology of Gabelica et al. (1983). The Si/Al ratio of the ZSM-5 zeolite used was 42, and ita X-ray diffraction pattern matched those reported in the related literature. The catalyst was used in the form of cylindrical pellets of approximately 2.5-mm diameter and 2.5-mm length. The composition of the catalyst pellets was 25 w t 9% zeolite, 35 wt 9% inert (fused alumina), and 40 wt 9% binder ( V e d 950, Kaiser). The bed length in all the experiments was 1.8 m. Different methanol flow rates, coolant flow rates, and inlet temperatures were used, thus conforming 14 runs. Mass balances were performed with the exit streams after reactor output was condensed: liquid hydrocarbon and aqueous phases and gaseous hydrocarbon phase. In order to calculate product distributions, the compositions of gaseous and liquid phases were analyzed by combined gas chromatography-mass spectrometry (GC-MS).
0888-5885/92/2631-0497$03.00/00 1992 American Chemical Society
498 Ind. Eng. Chem. Res., Vol. 31, No. 2, 1992
The catalyst for this study had been used previously in a number of cycles of reaction-regeneration. The catalyst for runs A1 to A3 (Table 111) had been already regenerated once by burning off coke in air at 500 OC before these W, and that for runs B1 to B11 had already been regenerated three times.
Table I. Parameters in the Kinetic Model [14]0 i bi,o Ei/(kJ kmol-') 1 23.30 129 400 2 26.75 139 OOO 3 24.15 122 200 4 18.58 93 800
Results and Discussion Reactor Model. The same unit was simulated in previous studies to analyze the existence and the a priori determination of limiting conditions for pseudoadiabatic operation (Ravella and de Lasa, 1987). Both one-dimensional and two-dimensional pseudohomogeneous models were used (de Lasa et al., 1986; Ravella et al., 1989). In the present study, a one-dimensional representation was applied for the simulation. The main hypotheses on which it is based were already justified in detail in previous contributions (e.g. Soria-Lopez et al., 1981; de Lasa et al., 1985, 1986). These assumptions can be summarized as follows. (a) Mass and thermal axial dispersion effects may be neglected. (b) Concentration and temperature profiles between the catalyst pellets and the gas phase may be considered negligible (de Lasa et al., 1985). (c) The axial pressure drop in the bed is small as compared to the total pressure, so it can be neglected. (d) The physical properties of the reactant stream and coolant fluid were assumed to be constant. Average values were used to improve accuracy. (e) The overall heat-transfer coefficient, U,at the wall of the reactor is considered constant. The heat-transfer coefficient houtin the coolant side and the parameters a, (heat-transfer coefficient near the wall) and k,, (effective radial thermal conductivity) were estimated by means of proposed correlations (de Lasa et al., 1986), thus providing an initial value for the numerical regression method. (f)The enthalpy of reaction was assigned to the fmt step of the kinetic model employed, conversion of oxygenates to light olefins, as described below. This simplifying assumption could be supported by calculations of the heat of reaction done as a function of product distributions. For example, in run B6 (Table III), the heat generated by methanol dehydration to dimethyl ether and formation of light olefins account for at least 70% of the total heat evolved in the reaction. This is consistent with previous reported data showing that most of the heat of reaction is released in the dehydration stages of the reaction network (Chang and Silvestri, 1977; Lee et al., 1986). The values of total enthalpy changes as a consequence of the reaction, AH, were calculated using classical thermodynamics from the heats of formation for products and reactants in each run. Furthermore, in the calculations, AH was considered a linear function of oxygenate conversion, as shown in Table 11. The unit's overall heat balance in each run allowed a calculation of heat losses. (9) It was assumed that a uniform coke content exists inside the reactor, which was proximately confirmed by determinations of the amount of coke formed along the reactor bed after different runs (Ravella, 1987). In this respect it should be pointed out that a higher activity with a thermal wave moving through the reactor was observed for the fresh catalyst during the first hours of operation. The activity in the catalyst bed stabilized after a period of several hours of reactor conditioning (Ravella, 1987). Kinetic Model. The kinetic expression for methanol conversion to hydrocarbons used was developed by Sedran et al. (1990b) for the same catalyst and using experimental information from a Berty reactor. This model comprises
aKinetic constants expressed as ki,o = ebijoe-EiIRT((kmol of atoms) h-' (kg of cat)-'). The temperature range was 302-370 "C.
four elementary steps: the conversion of methanol and dimethyl ether (A, oxygenate lump) to ethene (B), propene (C) and butenes (D) and the subsequent reaction of each olefin with the light olefin lump (01= B + C D) to form aromatics and paraffins (F). The model can be described by means of the following set of statements: A-B+C+D; 3kl (1) B + 01-F; k2 (2) C 01-F; k3 (3) D + 01-F; k4 (4) All the calculations with this model were done using a water-free basis. Species concentrations are expressed as the number of C atoms in one given species in relation to the total number of C atoms in the reacting system. Thus, by means of the four kinetic constants ki and the energies of activation of the corresponding reactions, it is possible to describe the composition of the complex effluent resulting from the catalytic conversion of methanol to hydrocarbons in terms of carbon concentrations of oxygenates, ethene, propene, butenes, and aromatics plus paraffins. Furthermore, to introduce the activity decay, an exponentialdeactivationfunction was assigned to each step of the kinetic model (Sedranet aL, 199Ob),the deactivation variable being the cumulative amount of hydrocarbons formed per unit mass of catalyst. Table I shows the kinetic parameters thus obtained for this model. Differential Balances of the Fixed-BedUnit. Mass Balances. Differential mass balances can be considered for each one of the chemical species included in the reaction of methanol conversion, as follows: oxygenates: dA/dz = -3LA exp(bl - E l / R T ) (5) ethene: dB/dz = LA exp(bl - E l / R T ) - LB(O1) exp(b2-E,/RT) (6) propene: dC/& = LA exp(bl - E l / R T ) - LC(O1) exp(b3-E3/RT) (7) butenes: m/dz = LA exp(bl - E l / R T ) - LD(O1) exp(b, - E 4 / R T ) (8) aromatics plus paraffins: F = 1- A - B - C - D = 1 - A - 01 (9) with L = bMMept,Ar2/FMe. Heat Balances. Two heat balances can be formulated for a reactor-exchanger with reactant and coolant circulating in fully cocurrent flow, as it is the case for the pseudoadiabatic reactor. inside the reactor (gas side): dT/dz = 3MA exp(bl - E , / R T ) - N ( T - T,) (10) outside the reactor (coolant side): dT,/dz = Q(T - T,) + Q1 (11)
+
+
Ind. Eng. Chem. Res., Vol. 31, No. 2, 1992 499
E1
Table 11. Physical Properties and Data Used in the Simulation M,,/(kg kmol-') 29.34 CpJ(kJ kg-' K-') 2.10 *,/(kg m-' h-') 0.0715 k,/(kJ h-' m-' K-l) 0.167 C, /(kJ kg-' K-') 2.34 ~ , f ( k m-' g h-9 1.7412 k,/(kJ h-' m-l K-l) 0.406 p,/(kg w3) 894 Pb/(kg m-3) 850 dP/m 0.0028 r/m 0.01045 D*/m 0.019 P/kPa 115.5 AH/(kJ kmol-'), 100% conversion -50550
AH
I-
= -loo00 - 40550(1 - A) (kJ kmol-'), for A 5 0.11
z=O
A = l
T = TO
320 'L
A X I A L POSITION ( m ) Figure 1. Run B5. Simulation of temperature (2') and concentration profiles as a function of reactor length: (+) experimental average temperature, (A)experimental relative carbon concentration of aromatic plus paraffins (F)at the reactor exit, ( 0 )experimental relative carbon concentration of ethene plus propene plus butenes (Ol), (A)experimental relative carbon concentration of ethene (B) (m)experimental relative carbon concentration of butenes (D) and (0) experimental relative carbon concentration of oxygenates (A).
The Variock kinetic and physicochemical parameters involved in eqs 5-11 are listed in Tables I and 11. The heat generation of the reacting system was, as previously discussed, assigned to the first step of the kinetic model, the formation of light olefins from oxygenates, as shown in eq 10. The heat losses in the reactor were also taken into account by introducing the term Q1 (see Nomenclature Section) in eq 11. Heat losses were calculated from the difference between the heat of reaction calculated from the heats of formation of products and reactants and the one observed experimentally. Typical valuea for the heat losses in the particular unit configuration used in this project were about 26% of the calculated heat of reaction. Boundary Conditions.
At
W
A
0.8 1.2 1.6 2.0 A X I A L POSITION (rn) Figure 2. Run B1. Simulation of temperature (2') and concentration profiles as a function of reactor length. For symbols refer to Figure 1. 0.0
0.4
B=C=D=Ol=F=O
T,= T,,O
(12)
These boundary conditions reflect the fact that the reactant was pure methanol and the initial temperature of both reactant and coolant were slightly different. The possible influence of different inlet coolant and reactant temperatures on pseudoadiabatic operation was already considered by de Lasa et al. (1989). The procedure for solving eqs 5-11 with the boundary conditions described in eq 12 was divided in two separate computer programs. In the first program, the assessment of the kinetic parameter bl (oxygenate conversion to light olefins) was first performed by solving the mass balance for oxygenates, eq 5, while allowing a maximum error of 5% in the resulting oxygenate conversion. The reaction rate term in this equation was evaluated using the experimentally averaged temperature profile (linearization for T between points of temperature readings). Then, the value of U was optimized against the experimental axial temperature profile, the objective function being the minimum value for the sum of the squared differences betweene experimental and theoretical temperatures. The initial guess in the U optimization routine was the value given by known correlations (de Lasa et al., 1986) for the experimental conditions of each run. The bl value used was the one coming from the first step. This procedure allowed one to decouple the assessment of bl and U, thus avoiding the problem of high correlation between kinetic and heat-transfer parameters when determined simultaneously (Martinez et al., 1985). In the second computer program, using the values of bl and U resulting from the first program, the kinetic parameters b2, bS,and b4 which satisfied the experimental product distributions were calculated. The strategy of
A X I A L POSITION ( m ) Figure 3. Run A2. Simulation of temperature (2') and concentration profiles as a function of reactor length. For symbols refer to Figure 1.
solution adopted in this study was appropriate considering that it decoupled the evaluation of kinetic and heattransfer parameters and that the largest contribution to the heat of reaction was given by the oxygenate conversion to olefins. The numerical integration in both programs utilized a fourth-order Runge-Kutta algorithm. The regression analysis was carried out employing a Marquardt optimization routine. The computer programs' outputs presented theoretical profiles for the concentration of the kinetic species as well as the temperature profiles (experimental and predicted) for each run. Results of the simulation are summarized in Table 111. A sensitivity analysis was performed on the optimized U values for changes in the observation of singular experimental temperature data, assuming an experimental error of f l OC. The observed average change in U was *3.28%. Examples of both concentration and temperature profiles are also presented in Figures 1-3. Different regimes
500 Ind. Eng. Chem. Res., Vol. 31, No. 2, 1992 Table 111. Computations of Kinetic Parameters and Optimization of Overall Experimental Conditions methanol coolant exptl flow rate/ flow rate/ oxygenate run no. (kg h-l) inlet ternp/'C conv/% bl 14.10 310.6 20.17 A1 0.1349 92.3 19.80 8.00 310.9 0.0878 99.9 A2 311.0 20.18 8.00 0.1623 98.0 A3 19.73 6.57 321.6 0.1045 98.2 B1 19.91 320.3 7.30 0.1473 90.5 B2 322.2 19.64 0.1140 5.00 96.2 B3 19.94 0.1757 7.50 318.7 88.9 B4 19.73 0.1266 5.70 320.2 92.0 B5 19.50 4.60 322.0 0.1306 89.2 B6 326.1 19.43 0.1159 4.60 96.1 B7 327.7 19.66 0.1900 4.60 90.4 B8 19.53 0.1465 4.60 326.4 90.7 B9 6.10 325.8 19.59 0.1346 B10 94.8 330.0 19.31 0.0989 4.60 99.9 B11
were observed for the experimental temperature profiles: the full pseudoadiabatic operation (PO, Figure l), the pseudoadiabatic operation for the average temperature (POAT, Figure 2; Ravella and de Lasa, 1987), and the hot-spot regime (maximum at finite axial reactor position, MFARP, Figure 3). In all cases, as can be seen in Figures 1-3, the simulated temperature profiles are quite close to the experimental ones. However, when a hot spot is developed, the simulation is less accurate (Figure 3), although it still is in a close proximity. The optimized values for the overall heat-transfer coefficient U were higher than those calculated by correlations. This is not surprising, since, from the three coefficients involved in the determination of U (bout, a,, and k,,), both a, and k,, could present strong variations, depending on the correlation used for their calculation (Froment and Bischoff, 1979). This is particularly true when the particle Reynolds number for the gas phase is around 15, which is an average value for these experiments. Although there is some dispersion, it can be seen in Table I11 that the optimized U values follow the trend implied by the values coming from correlations. The kinetic constants calculated in this study showed no severe inconsistency with the kinetic model's concepts. The average kinetic constant values bl to b4 from runs A1 to A3 (catalyst regenerated once) are 20.05, 23.74, 20.76, and 15.61, respectively. These constants are higher than the average kinetic constant values from runs B1 to B11 (catalyst regenerated three times) which are 19.63,22.41, 19.68, and 15.31, respectively. Thus an irreversible deactivation is suggested to explain this difference. This irreversible deactivation, encountered after each regeneration (Ravella, 1987), is a characteristic condition for this ZSM-5 catalyst. Moreover, for each set of runs (Al-A3 and Bl-Bll), the four parameters seem to oscillate from run to run around an average value without a definite trend. For example, in the case of runs B1-B11, as presented in Figure 4, b,, b2, b,, and b4 vary randomly around the values of 19.63 f 1.63, 22.41 f 6.11, 19.68 f 5.23, and 15.31 f 2.70%. This fact shows the adequacy of the proposed kinetic representation to model the conversion of methanol in the pseudoadiabatic reactor (the original model was developed in a Berty reactor unit). It should be pointed out that if the model is adequate or there is not significant deactivation in a given set of runs (the case of our study), the four constants should stay at constant levels without strong oscillations. This is certainly the tendency observed in the present study. The bi values obtained with the simulation agreed well with the ones obtained in a Berty reactor (Sedran et al., 1990b; refer to Table I). First, the relative magnitude of
Heat-Transfer Coefficients for Different kinetic param 23.26 24.56 23.39 22.85 21.26 22.67 21.04 22.42 22.50 22.99 22.18 22.38 23.32 22.96
23-
o
0
21 -
0
17n '
19 -
0
optimized 254.4 178.0 324.2 260.5 360.0 315.5 230.8 262.0 185.1 238.9 273.6 181.3 311.3 163.0
b4 15.55 15.72 15.55 15.27 15.37 15.14 15.42 15.24 15.24 15.43 15.32 15.14 15.73 15.11
20.58 21.14 20.57 20.12 19.33 20.01 18.65 19.45 19.41 20.33 19.29 19.46 20.24 20.27 ~
o
-
o
I
'
-
0
; O'".C*-p-.&Ps=.--
a~
7
A
,5 -A-A-A-A-~-A-A13
~ Oo O -
I
'
I
'
'
A
AA
I
'
-
I
-
calcd 173.8 144.0 179.6 151.4 172.3 152.8 183.7 160.3 158.9 152.6 180.4 165.3 164.6 144.4 o
~
Ind. Eng. Chem. Res., Vol. 31, No. 2, 1992 501 the present research, optimum light olefin yields (about 40-48% C atom distribution in the conditions employed and a maximum of 56.5% in the case of run B4) could be obtained under pseudoadiabatic operation conditions. Conclusions A new kinetic scheme for methanol conversion to hydrocarbons was found appropriate in the simulation of a pilot-plant pseudoadiabatic unit. The simulation not only produced good temperature profiles inside the reactor but also allowed the prediction of the exiting product distribution. The model also showed concentration profiles in the reactor which suggest that under pseudoadiabatic operation the production of light olefins Cz-C4can be achieved selectively. Acknowledgment We-are grateful to Consejo Nacional de Investigaciones Cientificas y TBcnicas de la Reptiblica Argentina for awarding U.S. an External Fellowship. This study was developed during the tenure of this fellowship. The authors also acknowledge the financial support of the Natural Sciences and Engineering Research Council of Canada. Nomenclature A = relative carbon concentration of oxygenates kinetic lump (methanol and dimethyl ether) (C atoms in oxygenates/C atoms in mixture) B = relative carbon concentration of ethene (C atoms in etheneIC atoms in mixture) C = relative carbon concentration of propane (C atoms in propene/C atoms in mixture) Cpc= coolant heat capacity (kJ kg-' K-l) Cp,, = gas-phase heat capacity (kJ kg-' K-l) D = relative carbon concentration of butenes (C atoms in butenes/C atoms in mixture) De = equivalent diameter for heat transfer (m) Ei = energy of activation for reaction i = 1-4 (kJ kmol-') F = relative carbon concentration of aromaticsplus paraffins (C atoms in aromatics plus paraffins/C atoms in mixture) F, = coolant flow rate (kg h-l) F M e = methanol mass flow rate (kg h-l) L = MM,pbw2/FMeparameter used in the one-dimensional reactor model (kg h kmol-l m-l) M = -AHpbrr2/FMeCp parameter used in the one-dimensional reactor modef (kg h K kmol-' m-l) MM, = methanol molecular weight (kg kmol-') N= , parameter used in the one-dimensional reactor model 6-l) 01 = relative carbon concentration of olefins (B + C + D) (C atoms in olefins/C atoms in mixture) P = total pressure (atm) Q = 2 U ~ rWcCp,, / parameter used in the one-dimensional reactor model (m-l) &I= (m*eor- MexpP'Me(1- Aexit)/WMeCp,FcZ), z ) , heat loss (Kim) R = gas constant (kJ kmol-' K-l) T = average temperature for the cross section (K) To= reactant inlet temperature (K) T,= coolant temperature (K) Tc,o= inlet coolant temperature (K) U = [(l/hout) + (llcu,) + (r/4ker)]-l, overall heat-transfer coefficient (kJ h-l m-2 K-l) Ucdc= overall heat-transfer coefficient as calculated from correlations (kJ h-I m-2 K-') W , = coolant mass flow rate (kg h-l) 2 = reactor length (m) bi = natural logarithm of preexponential kinetic factor for reaction i = 1-4
bi,o= natural logarithm of preexponential kinetic factor for reaction i = 1-4 (nondeactivated value) dp = particle diameter (m) h, = heat-transfer coefficient in the coolant side (kJ h-l m-2 K-1) k, = thermal conductivity of coolant (kJ h-l m-l K-l) k,, = effective radial thermal conductivity (kJ h-' K-l) k,, = thermal conductivity of gas phase (kJ h-' m-l K-l) ki = kinetic constant for reaction i = 1-4 ((kmol of C atoms) kg-l h-l) ki,o = non deactivated kinetic constant for reaction i = 1-4 ((kmol of C atoms) kg-' h-l) r = reactor radius (m) z = axial coordinate (m) Greek Symbols a, = heat-transfer coefficient near the wall (kJ h-' m-2 K-l) 6 = dimensional unit constant (kmol kg-' h-l) Pb = bed density (kg m-3) pc = coolant density (kg m-3) p8"-= gas-phase viscosity (kg h-' m-l) p, coolant viscosity (kg h-' m-l) AHkor = enthalpy of reaction assessed with enthalpies of formation (kJ mol-') AHexp= enthalpy of reaction observed experimentally (kJ mor1)
-
Registry No. MeOH, 67-56-1.
Literature Cited Avidan, A.; Edwards, M. Modelling and scale up of Mobil's fluid-bed MTG process. In Fluidization V ,Proceedings of the Fifth Engineering Foundation Conference on Fluidization, Elsinore, Denmark; Ostergaard, K., Sorensen, A., Eds.; Engineering Foundation: New York, 1986; pp 457-464. Borio, D.; Gatica, J.; Porras, J. Wall-cooled fixed-bed reactors: parametric sensitivity as a design criterion. AZChE J. 1989, 35, 287-292. Chang, C. Hydrocarbons from methanol. Catal. Rev.-Sci. Eng. 1983,25, 1-118. Chang, C.; Silvestri, A. The conversion of methanol and other 0compounds to hydrocarbons over zeolite catalysts. J. Catal. 1977, 47,249-259. de Lasa, H. Pseudoadiabatic reactor for exothermic catalytic conversions. Canadian Pat. 1,223,895, 1987. de Lasa, H. Pseudoadiabatic reactor for exothermic catalytic conversions. US. Pat. 4,929,798, 1989. de Lasa, H.; Ravella, A.; Rost, E. Converting methanol into gasoline in a novel pseudoadiabatic catalytic fiied-bed reactor. Proceedings of the 35th Canadian Chemical Engineering Conference, Calgary, Canada; 1985; Vol. 2, pp 102-107. de Lasa, H.; Ravella, A.; Rost, E. Pseudoadiabatic operation of a fixed-bed catalytic reactor for the conversion of methanol into gasoline. In Proceedings of the XVI ICHMT Symposium on Heat and Mass Transfer in Fixed and Fluidized Beds, Dubrovnik, Yugoslavia; van Swaaij, W., Agfan, N., Eds.; Hemisphere Publishing Co.: Washington, DC, 1986; pp 645-655. de Lasa, H.; Ravella, A.; Rost, E.; Mahay, A. Operation of coaxially cooled fixed-bed catalytic reactors: conditions of existence of the pseudoadiabatic regime. Chem. Eng. Sci. 1989,44, 1221-1226. Froment, G.; Bischoff, K. Chemical Reactor Analysis and Design; J. Wiley & Sons: New York, 1979; Chapter 11, p 532. Gabelica, Z.; Blom, N.; Derouane, E. Synthesis and characterization of ZSM-5 type zeolites 111. A critical evaluation of the role of alkali and ammonium cation. Appl. Catal. 1983,5, '227-248. Lee, W.; Sapre, A.; Yurchak,S. Process for convertingmethanol into olefins. Canadian Pat. 1,202,986, 1986. Maiden, C. A project overview. CHEMTECH 1988,1, 38-41. Martinez, 0.;Pereira Duarte, S.; Lemcoff, N. The modelling of fiied bed catalytic reactors. Comput. Chem. Eng. 1985, 9, 535-545. Nikolov, V.; Anastasov, A. A study of coolant temperature in an industrial reactor for o-xylene oxidation. AZChE J. 1989, 35, 511-513. Ravella, A. PO reactor for the conversion of methanol to hydrocarbons. Ph.D. Dissertation, The University of Western Ontario, London, Ontario, Canada, 1987.
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Znd. Eng. Chem. Res. 1992,31,502-508
Ravella, A.; de Lasa, H. The pseudoadiabatic regime for catalytic fiied-bed reactors: the limiting operating conditions. Chem. Eng. J . 1987,34, 47-53. Ravella, A.; de Lasa, H.; Mahay, A. Operation and Testing of a Novel Catalytic Reactor Confiiation for the Conversion of Methanol to Hydrocarbons. Ind. Eng. Chem. Res. 1987,26, 2546-2552. Ravella, A.; de Lasa, H.; Mahay, A. Pseudoadiabatic axial thermal profiles in a catalytic fixed-bed reactor: measurement and modelling. Chem. Eng. J. 1989,42, 7-15. Sedran, U.; Mahay, A.; de Lasa, H. Modelling methanol conversion to hydrocarbons. Revision and testing of a simple kinetic model.
Chem. Eng. Sci. 1990a, 45, 1161-1165. Sedran, U.;Mahay, A.; de Lasa, H. Modelling methanol conversion to hydrocarbons. Alternative kinetic models. Chem. Eng. J. 1990b, 45,33-42. Soria-Lopez,A.; de Lasa, H.; Porras, J. Parametric sensitivity and runaway in fixed-bedcatalyticreactors. Chem. Eng. Sci. 1981,36, 285-291. Received for review March 29, 1991 Revised manuscript received September 18,1991 Accepted September 25, 1991
Step-Response Kinetics of Methanation over a Ni/A1203Catalyst Rajiv Yadav and Robert G. Rinker* Department of Chemical and Nuclear Engineering, University of California, Santa Barbara, California 93106
Detailed experimental observations and interpretations of the transient behavior of methanation resulting from step changes in feed composition to a gradientless reactor are presented. The step responses clearly show that there is a continuous transition of the most abundant reactive intermediate on the nickel catalyst surface, going from mainly CH groups to mainly atomic carbon, depending on whether the H 2 / C 0 molar ratio in the feed is high or low, respectively. When that ratio is stoichiometric, which is close to optimal for steady-state operation, both intermediates are important. On the basis of these results, a phenomenological mechanism for methanation is proposed and accounts for both direct and hydrogen-assisted dissociative adsorption of carbon monoxide.
Introduction Transient response methods using step changes in feed concentration to study catalysis kinetics have been in use for over 50 years. In ita present form, however, the technique received ita main impetus from the work of Bennett in the USA and that of Kobayashi and Kobayashi in Japan. Both groups have summarized their own work and that of others in the area of transient kinetics in a number of publications (Bennett, 1976,1982; Kobayashi and Kobayashi, 1974; Kobayashi, 1982). Over the past decade, transient step response methods have been popular tools for explicating methanation kinetics. Some important findings from the literature are summarized in Table I. As can be seen from the table, it appears that the surface is covered by two forms of carbon during methanation, one less active than the other. However, opinion on the nature of these two carbon species is divided. Using an isotopic switching technique between hydrogen and deuterium on a methanation catalyst containing nickel on kieselguhr,Happel et al. (1982) concluded that two CH, species, x = 0 and 1, were abundant on the surface. These authors reported that coverage by C* ( x = 0, carbidic species) declined rapidly to a small fraction of monolayer coverage as the CO/H2 ratio was decreased, although coverage by carbidic species increased with increases in temperature. The coverage of CH* ( x = 1) species was found to be higher than that of C*. The presence of the CH species ( x = 1)was also indicated by Galuszka et al. (1981), and using multiple reflectance IR spectroscopy, Hayes et al. (1985) also identified CH as an abundant surface species. However, working with Ni/ A1203 catalysts, Underwood and Bennett (1984) and Stockwell et al. (1988) concluded that the catalyst was mainly covered by CH, ( x = 0) species. These authors proposed that the surface was likely covered by adsorbed CO and carbidic carbon, with CO being less reactive than the carbidic carbon. Part of their reason for proposing a
*Towhom all correspondence should be addressed.
value for x of 0 was based on the argument that no IR bands were observed in the C-H region. Another important finding that can be seen from Table I is that the amount of surface carbon decreases with increasing temperature (Happel et al., 1982; Underwood and Bennett, 1984). It can also be seen from Table I that studies reported in the literature have been done under differing CO/H2 ratios, temperatures, and space velocities. It was perceived that a systematic understanding of the effect of these variables on the nature of the methane response to step changes in feed concentration may be valuable, and this study was directed toward acquiring such an understanding. In that spirit, step response experiments were conducted over a wide range of CO/H2 ratios, two temperatures, and two space velocities, as can be seen from Table 11,which gives the range of experimental parameters used in this study. In summary, it is shown that the methane response and the nature and coverage of reactive intermediates depend on the CO/H2 ratio in the steady-state feed, as well as on the temperature and the space velocity. Above all, it is shown that the coverage by reactive surface species can be characterized with reference to the optimum steady state (OSS). The use of the OSS as a reference for characterizing the transient response is novel and should serve as a valuable, unifying tool for studies in transient kinetics. The concept of the OSS is defiied and discussed elsewhere (Yadav and Rinker, 1989, 1990b).
Experimental Details The catalyst used in this study was a commercial, proprietary BASF R1-10 Ni/Al2O3 catalyst. This is primarily a clean-up catalyst. The following nonproprietary information on the physical and chemical characteristics of the catalyst was supplied by BASF: surface area, -200 m2/g; pore volume, -0.45 mL/g; chemical composition on an anhydrous basis (wt %), -28 NiO, -9 S O 2 , -6 MgO, balance being A1203.Before being charged to the reactor, the catalyst was crushed to 14/18 mesh to ensure that
0888-5885/92/2631-0502$03.00 /0 0 1992 American Chemical Society
