Ind. Eng. Chem. Res. 1990,29,1167-1172
Literature Cited Flytzani-Stephanopoulos, M.; et al. Detailed Studies of Novel Regenerable Sorbents for High-Temperature Coal-Gas Desulfurization-I. Proceedings of the Sixth Annual Meeting on Contaminant Control in Coal-Derived Gas Streams, 1986; DOE/METC-86/6042. Focht, G. D.; Ranade, P. V.; Harrison, D. P. Chem. Eng. Sci. 1988, 43, 3005. Focht, G. D.; Ranade, P. V.; Harrison, D. P. Chem. Eng. Sci. 1989, 44, 2919. Gangwal, S. K.; et al. Bench-Scale Testing of Novel High-Temperature Desulfurization Sorbents. Final Report, Contract DEAC21-86MC23126, US.Department of Energy: Washington, DC, 1988. Gangwal, S. K.; et al. Environ. Prog. 1989, 8, 26. Gibson, J. B.; Harrison, D. P. Ind. Eng. Chem. Process Des. Dev. 1980, 19, 231. Grindley, T. Sidestream Zinc Ferrite Regeneration Testing. Pro-
1167
ceedings of the Seventh Annual Gasification and Gas Stream Cleanup Systems Review Meeting, 1987; DOE/METC/6079. Grindley, T.; Steinfeld, G. Development and Testing of Regenerable Hot Coal-Gas Desulfurization Sorbent. DOE/METC/16545-1125, 1981. Lew, S.;Jothimurugesan, K.; Flytzani-Stephanopoulos,M. Znd. Eng. Chem. Res. 1989,28,535. Sa, L. N.; Focht, G. D.; Ranade, P. V.; Harrison, D. P. Chem. Eng. Sci. 1989, 44, 215. Schmidt, D. K.; et al. Fluidized Bed Coal Gasification with Hot Gas Cleanup. Proceedings of the Eighth Annual Gasificationand Gas Stream Cleanup Systems Review Meeting, 1988; DOE/METC88/6092. Westmoreland, P. R.; Harrison, D. P. Enuiron. Sci. Technol. 1976, 10, 659.
Received for review June 7 , 1989 Revised manuscript received January 29, 1990 Accepted February 21, 1990
Reaction between H2S and Zinc Oxide-Titanium Oxide Sorbents. 2. Single-Pellet Sulfidation Modeling K. Jothimurugesan and D. P. Harrison* Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803- 7303
In the temperature range of primary interest, 650-760 "C,the reaction between H2S and a desulfurization sorbent composed of 1.5 Zn0:l.O TiOz (designation L-3140) can be described by a special case of the unreacted core model in which the global reaction rate is controlled by mass transfer and product layer diffusion resistances. Effective diffusivities through the product layer predicted by the random pore model show reasonable agreement with best-fit effective diffusivities determined by numerical methods. Although the magnitudes of the predicted and best-fit values differ, on average, by about 33%, the observed effects of temperature and pressure are consistent with random pore model predictions. Mass-transfer coefficients predicted by a modified Froessling equation differ from best-fit values by an average of only 15%. However, neither the effect of pressure nor the effect of temperature is adequately described. This is attributed to the fact that chemical reaction resistance is not truly negligible near the beginning of the reaction so that best-fit mass-transfer coefficients actually reflect both mass-transfer and reaction effects. The processes that determine the global rate of a gassolid noncatalytic reaction within a single pellet are numerous and complex. Mass transfer of gaseous reactant from the bulk gas to the pellet exterior surface is followed by diffusion through the pores of the pellet and perhaps through a layer of solid product before the solid reactant is encountered and the surface reaction can occur. The reverse of this sequence must be followed for gaseous product to reach the bulk gas. The structural characteristics of the porous pellet are important in determining the rates of the various steps, and the process is further complicated by the fact that pellet structure may vary with the extent of the reaction. At sufficiently high temperatures, additional structural changes which are independent of reaction may be imposed by sintering. A general discussion of the importance of these phenomena is provided by Szekely et al. (1976). In spite of the overall complexity, it is often possible to describe the global rate in terms of relatively simple mathematical models that consider only the most important phenomena and neglect steps that contribute little to the global rate. Such an approach was adopted by Focht et al. (1988) in modeling the sulfidation reaction between H2S and single cylindrical pellets of zinc ferrite. A special case of the unreacted core model (Yagi and Kunii, 1955) in which the global rate was determined by the rates of mass transfer to the pellet surface and diffusion through
the porous product layer was used. A similar approach has proven to be successful in modeling the experimental sulfidation kinetics of L-3140 zinc oxide-titanium oxide sorbents reported in our previous paper (Woods et al., 1990).
Unreacted Core Model The unreacted core model requires that the reaction be confined to a surface separating the solid reactant core from an outer product layer. The initial reaction surface corresponds to the external surface of the pellet. The thickness of the product layer increases with time, producing a shrinking core of unreacted solid. Within the core of solid reactant, the concentration is unchanged from its initial value of CW,while within the product layer the solid reactant concentration is zero. The general sulfidation reaction can be represented by the following stoichiometry: A(g) + bB(s) products (1)
-
For the L-3140 sorbent of interest, the specific reaction is H2S(g) + 0.667(1.5Zn0.Ti02)
-
products
(2)
By considering the reaction to be isothermal and the pellet to be infinitely long, a simple algebraic relation exists
0888-5885/90/2629-1167$02.50/0 0 1990 American Chemical Society
1168 Ind. Eng. Chem. Res., Vol. 29, No. 7, 1990 1.001
lE'OtF-----------------------!
f
(L
3
k
1 E-031
k z 7 . 5 1 ~0
--
- k I
7.5 x 1 0 cm4/mol min
= 7.5 x
I
I
4
1
10'
O o. O b
Chemlcrl 20 Rbrctlon . .40
.802
I
.80
10
~
)O Frrctlonil Sulfldatlon
Figure 2. Variation of mass-transfer, diffusion, and reaction resistances with extent of reaction.
P=
C S 8
(7)
2bkmAcA0
The first term on the right of eq 3 represents the resistance associated with diffusion through the porous product layer. The second term describes the mass-transfer resistance, and the third term represents the surface reaction resistance. The model was originally proposed to describe a reaction wherein a nonporous reactant was surrounded by a porous product layer, in which case the reaction surface requirement would be automatically satisfied. However, in a porous reactant, the unreacted core model can reasonably be applied only when the transport resistances, i.e., mass transfer from bulk gas to pellet surface and diffusion through the porous product layer, control the global rate. If the surface reaction resistance is important, the reaction in a porous solid will occur in a zone of finite radial thickness, and the basic requirement of a reaction surface is not satisfied. A more complex reaction model would be necessary, e.g., the grain model (Szekely and Evans, 1970). The transport control condition is most likely to be satisfied at high reaction temperatures because of the greater temperature dependence of k than either kmAor De and well into the reaction after a product layer of finite thickness has been formed. These effects are illustrated in Figure 1 where the reaction effectiveness factor derived from eqs 3-8 is plotted versus the fractional extent of the reaction. rl is given by c
ueA
J
q = 1 corresponds to complete reaction control in which case the use of the unreacted core model for a porous pellet would be totally inappropriate, while 7 = 0 representa total transport control where the third term in eq 3 is truly negligible and the unreacted core model is appropriate. The calculations in Figure 1 are based upon typical values of kmA= 370 cm/min and De = 4.7 cm2/min (to be developed) and three values of k ranging from 7.5 X lo3 to 7.5 X lo5cm4/(mol-min). Since kmAand De are almost independent of temperature, the temperature effect can be seen by comparing the results as a function of k . In all cases, 7 is a maximum at the beginning of the reaction, decreases until a minimum is reached in the range of x 0.8, and then increases again as the reaction approaches completion. For k = 7.5 X lo3 cm4/(mol.min) (low temperature), application of the unreacted core model to a porous solid would be totally inappropriate since 7 varies between approximately 0.8 and 0.4. In contrast, for k = 7.5 X lo5cm4/(mol.min) (high temperature), the system should closely follow the unreacted core model because rl 5 0.04 throughout. For the intermediate value of k = 7.5 X lo4 cm4/(mol-min),the chemical reaction resistance is approximately 30% of the total initial resistance but decreases rapidly and is less than 10% of the total for much of the reaction. The unreacted core model, neglecting the chemical reaction resistance, should provide a reasonable description of this system, but transport parameters determined by numerically fitting experimental data would necessarily contain some aspects of the neglected chemical reaction term. The relative importance of each of the three resistances as a function of fractional extent of reaction is shown in Figure 2 using the same values of De and kmAas in Figure 1 and the intermediate value of the rate constant ( k = 7.5 X lo4 cm4/(mol.min)). Initially no product layer exists, and the unreacted core model requires that the pore diffusion resistance must be zero. At this time, the chemical reaction contributes 28% of the total resistance with the remaining 72% being supplied by mass transfer. As a product layer of finite thickness is formed, the pore diffusion resistance quickly increases and both the masstransfer and chemical reaction resistances decrease in importance. For example, at IC = 0.2, the total resistance is made up of 12% from chemical reaction, 28% from mass transfer, and 60% from pore diffusion. By the time x = 0.5, product layer diffusion contributes more than 80% of the overall resistance, and the chemical reaction resistance is less than 10%. In the sulfidation modeling which follows, the chemical reaction resistance has been neglected throughout so that
-
Ind. Eng. Chem. Res., Vol. 29, No. 7 , 1990 1169 the relationship between time and conversion is given by t = .f(x) + flx (10)
Table I. Structural Properties of L-3140 Zinc-Titanium Sorbent
De and kmA,and therefore a and p , have been estimated by using appropriate literature correlations and by numerically fitting the experimental data. One would expect the numerically determined values to differ from the true coefficients because of the neglected chemical reaction resistance. The impact is primarily concentrated in kmA since both mass-transfer and chemical reaction resistances are important early in the reaction. Numerically determined effective diffusivities should be closer to the true values since the error associated with neglecting the chemical reaction resistance decreases as the pore diffusion resistance becomes important.
Parameter Evaluation Most of the terms comprising a and fl are known (R, C A ~ , Cso,and b). Therefore, if kmA and De can be estimated, eq 10 becomes totally predictive. However, it has been shown (Focht et al., 1988) that the predictive approach produces only qualitative agreement with experiment and that treating a and /3 as best-fit parameters is necessary if quantitative agreement is to be achieved. Reasons for the lack of quantitative agreement are numerous. The problem of neglecting the chemical reaction resistance has already been discussed. The literature correlations for kmA and De are only approximate, and they are being applied in this study to situations far removed from those for which they were originally developed. The pellets tested had an aspect ratio of 5 (length to radius), and the error associated with the infinite cylinder assumption should be relatively small. Both the predictive and best-fit approaches to evaluating cy and are described below. Mass-transfer coefficients were estimated by using the Froessling equation (Hughmark, 1967) modified for cylindrical geometry:
Sh = 2.0 + 0.6Re0.5S~0.33 (11) The characteristic dimension was taken to be the radius of a sphere having a volume equal to the actual volume of the cylindrical pellet. This correlation makes no allowance for pellet orientation since such effects are unimportant for spheres. However, in this study, the major cylindrical axis was normal to the gas flow. The effective diffusivity in a porous pellet is defined by Dt De = 7
Since the pores of the L-3140 pellets are of the size such that both Knudsen and molecular diffusion mechanisms may be important, the diffusion coefficient was estimated from 1 / D = l / D m 1/DK (13)
+
In turn, D, was calculated by using the well-known Chapman-Enskog equation (Smith, 1981), while DK was estimated from DK = 19400~ G)1'2 T
-(
SBPP
Geometric models must be used to relate tortuosity to porosity. The random pore model (Wakao and Smith, 1962) is the simplest of such models and was used in this work. This model states that the tortuosity is the inverse of the porosity so that De = De2
(15)
oxide 3.6 0.37
BET surface area, m2/g pore vol, cm3/g porosity, dimensionless av pore diam, 8, pellet density, g/cm3
sulfide
5.6 0.24 0.48 1750 1.97
0.66
4200 1.73
... Predlctrd, Oxlde Propertlea
- - Predlcted, Sulflde Propertlea - Numrrlcal Evalurtlon 0.0
1
40
1
1
80
1
1
1
1
120 160 T h e , mln.
1
1
1
200
1
240
1
I
280
Figure 3. Comparison of experimental results and model predictions: run ZT34 at 705 " C and 20 atm.
Pellet structural properties play an important role in the estimation of the effective diffusivity. As shown in Table I, there are significant differences between the properties of the original oxide and the sulfide product. The tabulated sulfide properties represent average values over the temperature range of interest from the preceding experimental paper (Woods et al., 1990). Hence, the effective diffusivity was estimated with both oxide and sulfide properties. The best-fit values of krnAand De were determined by minimizing the sum of squares of the differences between the experimental and predicted fractional sulfidation, x , over the range 0 Ix I0.5. This maximum value of x was chosen to provide numerical consistency since several of 0.6. the runs were terminated at values of x
-
Modeling Results Table I1 provides a summary of reaction conditions and values of kmAand De estimated from literature correlations and numerical analysis for each of the sulfidation runs in the temperature range 650-760 "C. The predicted values show the independent effects of reaction temperature, pressure, and pellet diameter on the transport parameters. An increase in temperature results in an increase in both kmA and De, while increased pressure produces smaller values of both parameters. Reduction in the pellet diameter results in larger kmA but has no effect on De. Both parameters are independent of H2S concentration. Figure 3 compares the experimental sulfidation data with the model results by using three different methods of parameter evaluation. Two of the model results were obtained by using predicted values of kmA and De, one based upon oxide properties with the other based upon sulfide properties. The third model results were obtained by numerical evaluation of the constants as previously described. Figure 3 data represent run ZT34 at 705 "C and 20 atm with 0.25 vol % H2S in the reacting gas. The use of oxide properties to predict De clearly results in the global reaction rate being overpredicted. In contrast, reaction rate predictions based upon sulfide properties are lower than experimental. The best-fit approach provides
1170 Ind. Eng. Chem. Res., Vol. 29, No. 7, 1990 Table 11. Transport Parameters for L-3140Zinc Titanate Sulfidation from Literature Correlations and from Numerical Analysis predicted transport coeff reaction conditions De (oxide), De (sulfide), best-fit coeff kmAI run temp, "C pressure, atm % H2S pellet diam, in. cm/min cm2/min cm2/min k-, cm/min De, cm*/min 342 15.3 4.5 271 6.8 31 650 1 2.5 31,~ 32 1 705 2.5 372 16.2 4.7 302 8.0 3 L 3 33 1 404 17.2 4.9 489 5.8 760 2.5 116 1 34 342 15.3 4.5 245 7.1 650 2.5 3116 1 35 372 16.2 4.7 303 7.7 705 2.5 3116 1 36 2.5 404 17.2 4.9 452 6.3 760 V16 1 37 650 1.25 342 15.3 4.5 240 6.4 3iI6 1 38 705 1.25 372 16.2 4.7 341 7.0 3/16 1 39 760 1.25 404 17.2 4.9 406 6.4 3/16 1 338 15.3 4.5 245 6.0 40 650 0.5 3/16 1 41 705 0.5 370 16.2 4.7 331 6.2 3 1 16 1 42 403 17.2 4.9 372 6.5 760 0.5 3 1 16 1 43 705 0.25 369 16.2 4.7 339 5.1 3116 1 54 616 17.2 4.9 285 8.0 760 2.5 l/8 1 55 705 2.5 576 16.2 4.7 336 6.3 l18 1 56 650 2.5 513 15.3 4.5 339 4.4 l18 3 5 ZT29 650 0.5 90 5.5 2.2 115 2.2 116 3 5 ZT30 705 0.5 99 5.9 2.4 121 2.5 116 5 ZT31 760 0.5 107 6.4 2.6 103 3.5 3/16 ZT32 5 650 0.25 91 5.5 2.2 116 2.6 3116 10 ZT33 705 0.25 49 3.3 1.5 68 1.9 3116 ZT34 20 705 0.25 25 1.8 0.8 30 1.0 3116 20 ZT35 705 0.50 25 1.8 0.8 31 0.9 3/16 1.001
I
0.80
Tlmr, mln.
Figure 4. Comparison of experimental results and model predictions using best-fit values of the mass-transfer coefficient and effective diffusivity.
-
"perfect" agreement to x 0.5 and "good" agreement thereafter. The results shown in Figure 3 are typical of all modeling tests. Experimental data generally lie between the two sets of predicted results, with the predictions based upon sulfide properties being somewhat closer to the experimental data. The numerical method of parameter evaluation produces excellent agreement with experiment over most of the fractional sulfidation range. The latter statement is further illustrated in Figure 4 where the best-fit results are compared to experiment for four additional runs representing experimental conditions over a range of pressure (1-5 atm), mole fraction of H2S (0.0025-0.025),and pellet diameter (1/8-3/16 in.). Each run was conducted a t 650 "C. Discussion of Transport Parameters
Table I1 shows the best-fit values of k d both larger and smaller than predicted. On an overall average basis, the ratio of predicted to best-fit values is 1.14 f 0.34 (mean f standard deviation). For those runs carried out at 1atm using 3 / 16-in.-diameterpellets, the average ratio of pre-
dicted to best-fit kmA is 1.15 f 0.25 (mean f standard deviation). However, the best-fit values at these conditions show a much stronger temperature dependence than predicted by using the mass-transfer coefficient correlation. At 650 "C,the ratio of predicted to best-fit values of kd is 1.36 (average of four runs). The ratio decreases to 1.15 at 705 " C (average of five runs) and to 0.95 at 760 " C (average of four runs). This trend with temperature is consistent with the explanation that the best-fit kmA values differ from the true values in that they contain some component of the surface chemical reaction resistance. Since the surface rate term is highly temperature dependent, and since it would be most important a t the lowest temperature (650 "C), one would expect the largest deviation between predicted and best-fit values at this temperature. At 760 "C, the surface reaction resistance should be more truly negligible and the best-fit and predicted values of kmA are in better agreement. The fact that the predicted kmA is much greater than the best-fit value for the three runs using 1/8-in.-diameter pellets may also be explained on the basis that chemical reaction resistance becomes more important as pellet size decreases. The added resistance from chemical reaction would cause the apparent (best-fit) kd to be smaller than the true value. In contrast, an increase in pressure decreases the importance of the chemical reaction resistance relative to transport resistances, and the ratio of predicted to best-fit kmA for these runs is actually less than 1.0. Extension of the previous arguments suggests that the best-fit values of the effective diffusivity should be closer to the actual effective diffusivity; i.e., the neglected chemical reaction resistance term should have less impact on the best-fit De values. Inspection of the Table I1 data indicates that, with one exception (run 56), the best-fit values of De lie between the predicted values based upon oxide and sulfide properties and are generally much closer to the sulfide values. This is expected since diffusion actually occurs through a sulfide product layer. The apparent temperature dependence of De for the 1-atm test results is shown on an Arrhenius plot in Figure 5. The best-fit values at the three temperatures are represented by the mean f standard deviation of the four or five tests at each temperature. Predicted values based
Ind. Eng. Chem. Res., Vol. 29, No. 7, 1990 1171
.
Sulflde ,, '/
1 .oo-
.060
I
I
,080
1.000
I
I
I
1.020 1.040 1.060 1/T x I@. K-'
1
1.080
I. 0
Figure 5. Temperature dependence of the effective diffusivity.
upon the random pore model using both oxide and sulfide properties are shown for comparison. From this figure it is obvious that the temperature dependence is quite close to that predicted. The apparent activation energy based upon the best straight line through the data is 1400 cal/mol compared to 1470 cal/mol predicted by the random pore model. Alternately, the 1400 cal/mol activation energy is approximately equivalent to a temperature dependence of T" with n = 1. Equation 14 suggests a value of n = 0.5 when the controlling mechanism is Knudsen diffusion; similarly, the molecular diffusivity varies approximately The observed linear dependence with T is as T1.75. therefore consistent with diffusion under conditions where both molecular and Knudsen mechanisms are important. The sorbent structural properties of Table I also suggest that both mechanisms should be important. Other recent high-temperature desulfurization studies have reported that numerically determined effective diffusivities were reasonably linear on an Arrhenius plot but the apparent activation energies were greater than found in this study. For example, Tamhankar et al. (1981) reported an apparent activation energy of 4300 cal/mol for the reaction of H2Swith iron oxide, and Focht et al. (1988) found the apparent activation energy for the reaction between H2S and zinc ferrite to be 4540 cal/mol. Both studies were carried out at somewhat lower temperatures, and it is possible that the higher apparent activation energies were caused by a residual influence of the chemical reaction resistance. The effect of pressure on the apparent effective diffusivity at a constant sulfidation temperature of 705 "C is shown in Figure 6. Since the Knudsen diffusion coefficient should be independent of pressure and the molecular diffusivity inversely proportional to pressure, the random pore model suggests that should be a linear function of pressure. Although the number of high-pressure experimental tests is limited, it is obvious that a reasonably good straight line does result. In Figure 6, the point at 1 atm represents the average of the De values of the six experimental runs at those conditions from Table 11. Only a single run was conducted at each of the elevated pressures, and the results are plotted directly. The equation of the best straight line through the experimental points is
D;'
= 0.12
+ 0.046P
(16)
with De having units of cm2/min and P having units of atm. Once again the effective diffusivities predicted by the random pore model based upon oxide and sulfide properties are included in Figure 6 for reference purposes. The best-fit results lie between the two reference curves
1
5
I
I
1s Prraeuro, rtm.
10
I
20
Figure 6. Pressure dependence of the effective diffusivity.
and are generally much closer to the sulfide values.
Summary Over the temperature range of primary interest, 650-760 "C, the kinetics of the reaction between H2S and single cylindrical pellets of zinc oxide-titanium oxide sorbent (L-3140) can be described by a special case of the unreacted core model, which assumes that the global rate is controlled by resistances associated with mass transfer and product layer diffusion. The predicted values of the mass-transfer coefficient and the effective diffusivity based upon the structural properties of the sulfided product produce qualitative agreement with experimental data. Quite good quantitative agreement results when the model parameters are evaluated by numerical methods. The numerically determined values of De exhibit an apparent temperature and pressure dependence that is consistent with predictions of the random pore model. The numerical values of kmA exhibit a temperature dependence that is greater than that predicted by the modified Froessling equation. The disagreement is attributed to the influence of the highly temperature dependent chemical reaction resistance which is significant early in the reaction, and, consequently, affects the numerically determined values of k d . Acknowledgment This research was sponsored by the US. Department of Energy, Morgantown Energy Technology Center, under Contract DE-AC21-87MC24160to Research Triangle Institute. The modeling work was carried out by LSU under Subcontract 1-474U3971 from RTI. We acknowledge Suresh Jain and Steve Bossart of METC for their contributions to the research and M. C. Woods and S. K. Gangwal of RTI who conducted the high-pressure experimental tests.
Nomenclature b = stoichiometric coefficient, solid reactant, dimensionless CAc= molar concentration of gaseous reactant at the unreacted core, m 0 1 / ~ ~ C, = molar concentration of gaseous reactant in the bulk gas, mol/L3 Cso = molar concentration of solid reactant, mol/L3 D = diffusion coefficient, combination of molecular and Knudeen, L2/time De = effective diffusivity, L2/time D K = Knudsen diffusion coefficient, L2/time D, = molecular diffusion coefficient, Lz/time f ( r )= diffusion function defined by eq 4 g ( x ) = reaction function defined by eq 5
1172
Ind. Eng. Chem. Res. 1990, 29, 1172-1178
= mass-transfer coefficient, L/time k = intrinsic surface rate constant, L*/(mol-time) M = molecular weight of gaseous reactant, mass/mol P = pressure, force/L2 H = pellet radius, length R e = Reynolds number, dimensionless Sc = Schmidt number, dimensionless Sh = Sherwood number, dimensionless S , = sorbent specific surface area, L2/m t = time T = temperature x = fractional sulfidation, dimensionless k,,
Greek Symbols a = diffusion parameter defined by eq 6, time /3 = mass-transfer parameter defined by eq 7, time y = chemical reaction parameter defined by eq 8, time t = pellet porosity, dimensionless 17 = effectiveness factor, dimensionless pp = pellet density, mass/L3 T = tortuosity, dimensionless
Registry No. H& 7783-06-4;ZnO, 131413-2;Ti02,13463-67-7.
Literature Cited Focht, G. D.; Ranade, P. V.; Harrison, D. P. Chem. Eng. Sci. 1988, 43, 3005. Hughmark, G. A. AIChEJ. 1967, 13, 1219. Smith, J. M. Chemical Engineering Kinetics, 3rd ed.; McGraw-Hill: New York, 1981. Szekely, .J.; Evans, J. W. Chem. Eng. Sci. 1970, 25, 1091. Szekely, J.; Evans, J. W.; Sohn, H. Y. Gas-Solid Reactions; Academic Press: New York, 1976. Tamhankar, S . S.; Hasatani, M.; Wen, C. Y. Chem. Eng. Sci. 1981, 36, 1181. Wakao, N.; Smith, J. M. Chem. Eng. Sci. 1962, 17, 825. Woods, M. C.; Gangwal, S. K.; Jothimurugesan, K.; Harrison, D. P. Ind. Eng. Chem. Res. 1990, preceding paper in this issue. Yagi, S.; Kunii, D. Fifth International Symposium on Combustion; Reinhold: New York, 1955.
Received for review June 7 , 1989 Revised manuscript received January 29, 1990 Accepted February 21, 1990
Isomerization of Butenes as a Test Reaction for Measurement of Solid Catalyst Acidity And& T. Aguayo, J o s e M. Arandes, Martin O l a z a r , and J a v i e r Bilbao* Departamento de Ingenierla Qdmica, Universidad del Pais Vasco. Apartado 644, 48080 Bilbao, Spain
The theoretical and experimental steps necessary for the rigorous usage of the isomerization of n-butenes as a test reaction to measure the surface acidity of microporous solid catalysts have been developed. The experimental study has been carried out with six catalysts of silica-alumina prepared a t different levels of acidity strength. Between 155 and 200 " C and from the kinetic data obtained in the integral reactor, the kinetic constants of the reactions 1-butene to cis-butene, 1-butene to trans-butene, and cis-butene to trans-butene have been calculated. The calculated values have been compared with the values of the surface acidity measured following two conventional methods, the titration with n-butylamine in the liquid phase using Hammet indicators and the adsorption of tert-butylamine at a programmed temperature. The isomerization of butenes has been studied very often in the literature as a reaction model to ascertain the behavior of different catalytic systems and, as a last resort, to optimize their preparation based on the yield, selectivity, and desactivation found in the catalysts tried in the reaction model. A survey of the relevant literature shows that the isomerization of butenes is carried out on metals (Ragaini, 1974; Hisatsune, 1982; Mintsa-Eya et al., 1982), metal oxides (Uematsu et al., 1976; Nakano et al., 1979; Goldwasser and Hall, 1980, 1981; Rodenas et al., 1981; Goldwasser et al., 1981a,b; Rosynek et al., 1981; Van Roosmalen and Mol, 1982; Engelhardt et al., 1982),metal phosphates (Sakai and Hattori, 1976; Itoh et al., 1982), cation-exchanged zeolites (Langner, 1980; Nagy et al., 19781, and ion-exchanged resins (Uematsu et al., 1974). Using this model reaction, Ghorbel et al. (1974) determined that there was a relationship between the catalytic activity and the acid-base character of the catalysts. The existence of this relationship suggests that the usage of the isomerization of butenes as a test reaction to measure the surface acidity has advantages over the usage of other methods (Tanabe, 1970; Benesi and Winquist, 1978). Among these methods, the usage of indicators for acidbase titration (Benesi, 1956, 1957) assumes that equilibrium is reached and that this is not affected by the amount of indicator. Nevertheless, according to Deeba and Hall (19791, this is debatable for the case of catalyst titration
where one of the reactants is a solid surface. Moreover, it is a method that is difficult to apply with colored catalysts and with deactivated catalysts. Another limitation of Benesi's method is the difficulty in diffusing the organic base and the indicator in catalysts of small pore diameter (Kladnig, 1979; Barthomeuf, 1979). Other methods, such as calorimetric titration (Bezman, 1981) and desorption at programmed temperatures of chemisorbed bases (Bielanski and Datka, 1975; Takahashi et al., 1976; Schwarz et al., 1978), are basically subjected to many of the Benesi method limitations and require more complex experimentation. Nevertheless, they lead to more reproducible results. The carrying out of the isomerization of butenes as a reaction test requires relatively simple reaction equipment. Nevertheless, difficulties arise in the analysis and interpretation of kinetic data, which have been only partially solved in the literature. The steps necessary for an ideal application of the method can be summarized as follows: The first step is to delimit the reaction conditions in which the kinetic study is rigorous and reproducible. In this case, the reaction conditions must correspond to an easily measurable conversion of the different isomers (integral reactor) that must not be masked by the catalyst deactivation. The second step is to use a rigorous method to analyze the kinetic data obtained in the integral reactor, these data fitting a real kinetic model that takes into account the
0888-5885/90/2629-1172$02.50/0 0 1990 American Chemical Society
