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Measurement and Modeling of the Kinetics of Catalyst Decay in Fixed Beds: The Eurokin Survey John J. Birtill* Department of Chemistry, The UniVersity of Glasgow, Glasgow G12 8QQ, Scotland, United Kingdom
Experimental techniques for the practical measurement of catalyst decay are reviewed, and some gaps and needs are suggested for future progress. Catalyst decay kinetics in fixed beds can be modeled according to a hierarchy of techniques, from purely empirical to rigorously fundamental. Empirical modeling is usually preferred for practical industrial purposes. Besides the need to decouple reaction kinetics, decay kinetics, and any influence of pore diffusion, for slowly decaying catalysts, the slow rate of data acquisition is a limiting factor. Hence, there is a need for better equipment design and better procedures for the efficient and informative testing of catalyst decay. Table 1. Power-Law Decay Kinetics1
1. Introduction This review is a concise summary of the main findings of a study that was commissioned recently by the Eurokin consortium (www.dct.tudelft.nl/eurokin). The aim of the study was to define the current state of learning and best practice for the study of industrial catalyst decay kinetics and to present it in a structured, informative manner. The focus was on fixed catalyst beds with a long life. Much of the background information was collected from an extensive literature survey, covering >700 papers from the past 50 years. In this paper, for the purpose of brevity, references are made to previous literature for some concepts that have already been well-described. The requirements for industrial research and development include practical and efficient techniques for the experimental measurement of catalyst decay and the empirical modeling of decay kinetics. The end-uses include catalyst development, catalyst selection, prediction of catalyst life, and monitoring and optimization of process catalyst performance. From limited published information and background knowledge, it seems that industrial catalyst decay models typically involve significant theoretical approximation and make use of all available performance data including studies at the laboratory, pilot, and plant scale, post mortem characterization, and, in some cases, accelerated decay. Exact determination of catalyst decay kinetics is time-consuming and expensive, and so some compromise between scientific rigor and industrial pragmatism is inevitable, especially when testing multiple catalyst formulations at an early stage of development. Hence, simple empirical models are favored over fundamental models for plausible fitting to a limited range of data. However, as catalyst and process development becomes more advanced, progressively more accurate knowledge is required. Simple models may be adequate for catalyst selection and process design, but their reliability for extrapolation outside the experimental range is uncertain. The nature of the decay mechanism should be determined in any serious study of catalyst decay kinetics to provide some sense of the physical basis of an empirical rate law and hence also of its likely limitations. However, this paper is concerned mainly with decay kinetics, and so mechanistic aspects of decay and methods of characterization are considered only in outline with some additional thoughts under Gaps and Needs. * To whom correspondence should be addressed. E-mail:
[email protected]. Address: 15 Portman Rise, Guisborough TS14 7LW, UK. Phone: 0044 1287 638265.
activity decay
concentration dependence
decay rate-da/dt
activity-time a
independent m ) 1 independent m * 1 parallel/series General
none none reactant/product reactant/product
kda kdam kdCnam kdΨ(C)am
exp(-kdt) (1+ (m - 1)kdt)-1/ (m-1) complex complex
1 Activity is sometimes expressed mechanistically as a ) (S/S )p, where 0 S is the number of sites still active and p is the reaction site order. If the loss of sites -dS/dt ) kSΨ(C)Sq, then the activity decay can still be expressed in one of the previous forms by rearrangement: -da/dt ) pkSΨ(C)am, where m ) (p + q - 1)/p.
2. Catalyst Decay Kinetics Before describing test methods for catalyst decay kinetics, it is first necessary to consider the various types of models for catalyst decay that are in common use. The deactivation kinetics describes the variation of catalyst activity at each point in the catalyst bed in response to time, temperature, and composition of the fluid phase. The concept of separable reaction and decay kinetics is usually assumed to apply.1-3 This should be tested at various stages of decay,4 basically by showing that the reaction kinetics does not change during decay. The catalyst activity can also be related to the accumulated quantity of coke and the coking kinetics.5-8 The interrelation of the effects of pore-diffusion resistance and decay are considered briefly in section 5. In the absence of such effects, the following approaches are commonly used for describing the rate of activity decay. Table 1 shows examples of well-known empirical powerlaw deactivation kinetics and related activity-time expressions. Independent decay is not affected by the composition of the fluid phase, and so the decay rate is uniform along a fixed isothermal catalyst bed, although it usually varies with temperature.1-3,9 If the decay is composition-dependent, then the decay rate is not uniform along a fixed catalyst bed but varies with the local fluid composition as well as temperature.1-3 Independent decay kinetics can often be fitted wrongly if the range of data is inadequate (section 4). The use of these empirical expressions can be extended to include more complex cases such as a residual steady state activity,10,11 activation-deactivation,12 additive decay kinetics,1,3,13 multiplicative decay kinetics,13-15 and, in principle, bifunctional catalysts. However, as discussed in section 6, complex expressions require extensive data for plausible model
10.1021/ie060590v CCC: $37.00 © 2007 American Chemical Society Published on Web 03/13/2007
Ind. Eng. Chem. Res., Vol. 46, No. 8, 2007 2393 Table 2. Activity-Coke Expressions and Activity Decay Kinetics type
activity-coke dependence a
power-law decay kinetics -da/dt1
linear exponential hyperbolic
(1 - RCC) exp(-RCC) 1/(1 + RCC)
RkCCAna RkCCAna2 RkCCAna3
1 Same activity-coke relationship for coking and main reaction. This example: parallel coking: dCC/dt ) kCCAn
fitting. Some published studies describe the rapid initial loss of activity to a residual near steady-state, followed by slow decay. If the steady-state is influenced by reaction conditions, then this could be important for an industrial catalyst, but the long, slow decay in the main part of life is usually more important and more difficult to determine. Mechanistic poisoning/balance-of-sites expressions describe the loss of active sites due to poisoning by impurities or reaction byproducts. They are derived from decay mechanisms and may be complex and non-separable. Although they provide insight into poisoning decay, they often include too many adjustable parameters for practical models. Deactivation due to impurity poisoning can also be considered more simply in terms of axial poison conversion models16 with progressive loss of active sites. Empirical activity-coke relationships are used in combination with coking kinetics.5-8 Activity-coke relationships accounted for ∼25% of all experimental models found in the literature survey, and the exponential relationship was the most common. In practice, many catalysts accumulate quite large amounts of coke due to multilayer adsorption or polymeric structures and, in some cases, pore filling. The choice between empirical activity power-law decay kinetics and empirical coking kinetics with empirical activity-coke relationships is a matter of judgment. As shown in Table 2, these approaches are equivalent if the activity-coke relationship for the coking reaction is the same as for the main reaction.17 Some authors try both approaches.18 In general, the activity power-law expression provides a simpler, more direct statement of decay than the combination of coking kinetics with an activity-coke relationship. The additional error from the measurement of the coke content will increase the overall uncertainty in the decay model as compared to the activity power-law approach. The choice depends on questions of practicability, purpose, and benefit. (i) Can the coke content and coking kinetics be welldetermined? Although in many cases the bulk coke content can be determined accurately (e.g., gravimetrically or by complete oxidation to CO2) bed-average activity-coke data from integral reactors are not reliable for decay modeling (section 4). Moreover, not all the coke is necessarily deactivating. Methods for determining coking kinetics are discussed briefly in section 4. (ii) Why is it desirable to measure coke? Knowledge of coking kinetics might be important for various reasons, for example, when feed stock conversion to coke is significant, when detailed information on coke location and content is required for design purposes (e.g., regeneration or reactor pressure drop), for detailed modeling of intra-particle fouling (see following section and section 5), or for catalyst development. (iii) Is the additional insight justified by the additional effort? Various mechanistic justifications can be derived for activitycoke relationships. Frequently, however, the nature of the deactivation by coke is unknown or poorly characterized. An empirical activity-coke relationship is a correlation with unproven physical significance even if it fits well to some data sets. The relationship between coking and catalyst decay could
be indirect (e.g., coking rate is dependent on catalyst activity, but activity decay is caused by some other mechanism). In catalyst development, the coking kinetics may provide useful mechanistic insight into the influence of catalyst composition on catalyst stability. In some cases, selectivity may be related to the quantity of coke (section 3). The weakness of the activity power-law expression is that it contains no hint of the decay mechanism, and if the range of decay data is limited, then it might obscure and oversimplify complex decay kinetics. Activity power-law expressions are unsuitable when the impact of changes in pore diffusion is significant, in which case, if the decay is caused by fouling, it is necessary to study the fouling (coking) kinetics in relation to the pore structure to model the decay kinetics reliably (section 5). Empirical power-law expressions are also used to describe the loss of surface area due to metal particle sintering. The expressions are formally similar to those described previously for deactivation kinetics and may incorporate a residual term to describe an eventual steady-state dispersion.10,19 However, if the empirical activity-surface area relationship is nonlinear, due to the influence of different crystal faces or surface defects,20 then it will usually be more useful to model activity decay directly. Fundamental mechanistic models of particle sintering are difficult to develop and so are outside the scope of this work. Although there has been significant effort in the development of fundamental models of sintering, no examples of fundamental models of activity decay due to sintering were found. 3. Selectivity Change Selectivity may increase or decrease as a consequence of catalyst decay. If the selectivity-conversion plot at fixed temperature does not change, then any observed selectivity change is only apparent. The selectivity can be restored to its original value by increasing space time so as to restore the conversion to its original value.21 This type of selectivity change can be described by the reaction kinetics in combination with the deactivation kinetics. An intrinsic selectivity change is caused by a change in the relative rate constants of contributing parallel or series reactions due to a change in the fundamental nature of one type of active site or in the relative abundance of different sites or of multi-site clusters. Hence, a decay model might need more than one power-law expression or activitycoke relationship to describe the changing activity for different types of site and different types of reactions.5,8 Selectivity may also change due to changes in pore diffusion properties (section 5). 4. Experimental Techniques for Deactivation Kinetics To determine a realistic decay model, it is necessary to decouple activity and concentration effects in the rate equation.1-3 The main challenge is to measure a sufficient range of useful data that contains sufficient information for fitting a decay model. This requires decay tests with variation of space time W/F and feed composition according to a suitable plan. This discussion is limited to slowly decaying catalysts, and for these, the collection of sufficient data in a reasonable period of time is an additional challenge. The suitability of various types of reactors for the study of decay kinetics that is not affected by pore diffusion is summarized in Table 3. The capability of the equipment has been graded A-C for the ease of decoupling decay kinetics from reaction kinetics and for the range of data that is generated in each test period.
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Table 3. Suitability of Experimental Techniques for Studying Decay Kineticsa reactor type gradientless: Berty and Carberry, PFR with recycle
controlled variation of W/F feed composition
decouple reaction and decay
data range/ test periodb
% of exptl refs
yes
yes
A
C
20
no no yese yese yes yes yese
no yes no yes no yes yes in parallel tests
Cd Bd B A B A A
C C C C B B Ag
54 54 2 0 4
coking micro-balance flow-through micro-balance
yes yes
yes yes
B A
C C
5 4
pseudo-adiabatic single fixed-bed multi-zone fixed-bed
no yes
yes yes
B A
B B
2 1
fixed bed/plug-flow
fixed bed multi-portf rixed bed multi-portf parallel multi-tube fixed-bed reactors
1
other pros and consc commercial Berty and Carberry units; can test large pellets simple, inexpensive limited information more information but slow sequential work awkward construction; axial takeoff must be small commercial multi-tube units; can also vary T bypassingh commercial unit TEOM awkward construction.
} some information from axial T gradient
a Key: A ) good and C ) poor. b Range of conditions (C, W/F, T) per single test period. c Isothermality assumed unless adiabatic. d Better with p-m activity profile. e Tests at different W/F, not the deactivation-compensation method. f Can also configure reactor tubes in series, at the same or different T. g Parallel tests can cover a wide range of conditions (C, W/F, T) simultaneously. h Unreliable variation of W/F as the flow can bypass catalyst.
Obviously, uniform composition of the fluid phase is very desirable, and so gradient-less reactors of various types are ideal for systematic studies of decay kinetics.1,22a The reaction kinetics can easily be decoupled from the decay kinetics by maintaining constant composition during each test period by control of the reactor feed rate and feed composition. Although the reaction conditions can be varied over the course of an experiment, only one decay data point is measured for each test period, and so this approach is slow unless multiple reactor units are available for simultaneous tests. Integral, fixed-bed reactors are the most popular choice for catalyst research. They are easy to design, build, and operate. Many decay studies are carried out in these reactors with limited variation of experimental conditions, but it is not possible to discriminate between alternative decay models unless the composition dependence is shown by the data. Integral conversion data from a fixed catalyst bed give a bed-average value for activity and disguise the effect of any axial decay gradient.23,24 In some cases, independent decay (or activity-time) models can be fitted, even though a significant axial decay gradient develops over time.25 The deactivation-compensation technique (gradually increasing space time, constant conversion) can also be used to fit an independent decay model by selecting the analytical solution that gives the best fit to the integral data.1,2,26 However, this method is potentially misleading because composition-dependent decay will also give a linear plot.25 A simulated example for parallel decay is shown in Figure 1. The data have been fitted to a linear plot even though the activity profile within the bed becomes progressively less uniform with time. In general, independent decay models derived from single, integral tests are unreliable for process design and optimization. It is necessary to test for composition dependence by measuring the activity profile along the fixed bed over life and/or by variation of the feed composition. For fast decay, the activity profile in an integral reactor can be studied by carrying out successive experiments with different values of space time W/F (i.e., different catalyst charge or feed rate). The broad range of data can then be fitted by trial and error to alternative decay models.27,28 There are few examples of this approach in the literature. One example, which was part of a larger study, including tests under both differential and integral conditions, is shown in Figure 2. The integral tests were carried out at six
Figure 1. Application of deactivation-compensation method to integral reactor data. (a) Plot of ln (space time) against process time for simulated parallel decay. (b) Activity profile at various values of process time. Simulated data, parallel decay with m ) 1, decreasing feed rate to maintain fixed 98% conversion.
different space times and two temperatures. Each decay experiment lasted only 40 min, and so the sequence of 12 experiments could be completed quite quickly. In Figure 2b, the point activity values for W/F ) 2.0, relative to identical reaction conditions (i.e., same conversion) at t ) 0, are derived from the gradients (differential rate values) in Figure 2a. Although the overall data were interpreted in terms of parallel decay, the appearance of Figure 2a suggests series decay (i.e., decay is more severe at higher W/F). For slow decay, the sequential approach described previously is impractical, and it is necessary to generate multiple data points simultaneously during each test period. In a multi-port reactor, the local fluid composition and catalyst activity at various positions (i.e., different W/F) along the length of the reactor are monitored continuously using multiple sample ports.31,32 The flow rate of each sample stream must be very small as compared
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Coking kinetics is best studied in a microbalance. It is difficult with conventional equipment to avoid some degree of diffusion control within the catalyst sample,34 but the development of the flow-through tapered element oscillating microbalance (TEOM) has enabled reliable variation of space time in coking decay studies in a fixed-bed (∼plug-flow) reactor.32,34,35 Obviously, if the effect of temperature is to be included in a decay model, then isothermal decay tests must be carried out at several different temperatures. The ramped temperature, deactivation-compensation technique (increasing temperature to maintain constant conversion) is used in industry for catalyst screening and pilot tests because it mimics plant operation. However, as discussed previously, the results from integral, fixed-bed reactors disguise internal axial decay gradients and so are unsuitable for decay kinetics. The changing axial temperature gradient during a life test in an adiabatic33 or pseudo-adiabatic36,37 reactor can provide additional information about the activity decay gradient. Finally, the techniques in Table 3 can be used in combination to generate a broad range of information for a decay model (e.g., fixed-bed multi-port reactor and coking microbalance,32 adiabatic reactor with axial multi-port IR analysis and axial temperature measurement33). 5. Pore Diffusion Figure 2. Investigation of catalyst decay by experiments at variable space time in an integral reactor. (a) Integral conversion vs space time W/F. (b) Point activity at W/F ) 2.0 vs process time. Data for dehydrogenation of benzyl alcohol over 10% copper-0.5% chromia/asbestos catalyst, replotted from Corella et al.27
to the reactor flow or else compensation must be made in calculation of the downstream W/F. Alternatively, an in situ analytical probe can be used.33 This problem is also avoided by parallel testing in a multi-tube unit, simultaneously covering a range of space time and also feed composition.21 This technique has been used in industry for catalyst decay, but no published studies have been found. The further potential of parallel testing for catalyst decay is discussed further in section 8. If the catalyst is discharged in segments from a fixed bed after a decay test, then the post mortem activity decay profile can be determined from measurements in a laboratory reactor. This can be used in combination with the integral decay data for fitting a decay model. Indeed, in some cases, approximate catalyst decay kinetics can be derived from plant data by matching the post mortem activity profile of a process catalyst with the process reactor history.21 The use of pseudo-differential conditions (low integral conversion and so almost uniform composition) in a fixed bed is sometimes used for decay modeling, but this approximation is not valid if the small axial composition gradient (e.g., for a product) causes a decay gradient.28 For series decay, this gradient can be reduced by co-feeding reactants and products. Integral, fixed-bed reactors are often used for the study of coking decay, and bed-average values are determined, not just for activity but for coke content as well. Once again, these bedaverage values can disguise significant axial gradients within the bed, and so the use of bed-average coke content in the Voorhies relation6,29,30 or for bed-average activity-coke expressions is unreliable.7 It is necessary to determine the axial gradients of both activity and coke. A broad range of data can be collected by operation over a range of space time and composition. The axial coke content can also be determined by segmental discharge and post mortem analysis.
Decay kinetics is more complex when pore diffusion is a significant factor. The influence of an intra-pellet concentration gradient can lead to a nonuniform intra-pellet decay profile. Foulant deposits can reduce pore dimensions or even block pores. The pore structure of the pellet or the dispersion of a supported active phase can change due to sintering processes. These changes may lead to changes in observed selectivity, especially for consecutive reaction schemes. These mechanistic phenomena will not be described in detail, but a key consideration for practical studies is the degree to which the decay kinetics varies with particle size. Activity decay data can be measured and collated at the active site level (i.e., basic decay kinetics without diffusion effects (if possible)) and at the particle level, extending to effective pellet activity decay kinetics.8 Likewise, changes to selectivity can also be measured at both levels. Additional data to link these two levels of kinetics can be determined by fresh, in situ, and post mortem pellet characterization. The characteristics of some common cases (probably not all) of catalyst activity decay and the implications for testing have been categorized in Table 4. For cases I-III, useful decay tests can be carried out on crushed pellets, but some confirmatory tests on whole pellets are desirable, and a term is required for the pellet effectiveness factor for case III. For other cases, tests on crushed pellets might still be useful, but extensive testing over a range of particle sizes, including whole pellets, is required for a reliable empirical decay model. The choice of practical experimental techniques is limited (see section 8), and a lengthy program of work might be unavoidable. Tests can be carried out on various sizes of pellets in gradient-less reactors (Table 3) or in fixed beds, subject to the usual design criteria for particle and reactor dimensions, preferably with multi-port analysis for variation of space time and with segmental catalyst discharge. The activity, pore properties, and diffusion properties can be measured for fresh and discharged pellets and related to test conditions. If a catalyst test is carried out on a mixed range of particle sizes, then the segmentally discharged catalyst can be graded by particle size and retested for effective and intrinsic activity. This particle grading technique has been used for checking coke content
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Table 4. Testing Catalyst Activity Decay When Affected by Pore-Diffusion Resistance characteristics
case I
case II
case III
fresh pellet: pore resistance reduces activity uniform loss of active sites throughout the pellet decay reduces pore size and/or access
no yes no
no no no
examplesa useful to study crushed pellets need to test whole pellets for model need to include pellet effects in decay model
i ii yes yes yes check to confirm no effect no yes yes but not complex
yes yes no
case IV
case V
case VI
case VII/VIII
yes no no
no yes yes
yes yes yes
yes/no no yes
i, iii iv iv v may be useful for basic decay model, then vary particle size.b extensive testing necessary yes but may be complex
a Key to examples. i: Fast impurity poisoning (diffusion-limited). ii: Slow impurity poisoning. iii: Parallel or series poisoning. iv: Pore shrinkage (sintering). v: Foulant growth. b Crystallite size is an additional factor for some microporous solids.
against particle size,29 but no references were found for post mortem activity tests. If catalyst sample extractors are available at a pilot or commercial scale, then the post mortem characterization of catalyst pellets at various stages of decay can be related to the previous pellet history (C, T, t) within the process. The development of advanced NMR techniques for in situ and post mortem characterization is noted in section 8. In the single pellet diffusion reactor, the change in concentration of reactant across a pressed pellet slab is measured over time. 22b This technique has been used to assist discrimination between selfpoisoning (fouling) models. However, no recent references or examples of commercial application were found for this technique. If decay is due to any sort of fouling process, then it is necessary to study the fouling kinetics in relation to the diffusion characteristics, the particle size, and the pore structure to model the decay kinetics realistically.8 The theoretical problems associated with modeling irregular catalyst pore networks in microscopic detail are difficult. However, the growth of computing power has led to the development of progressively more complex theoretical catalyst decay models, including probabilistic models to describe changes to pore connectivity. 6. Simplicity versus Complexity: Model Discrimination The most suitable approach for decay modeling depends on the aims of the work, the effort required, and the value of the outcome. Many industrial catalysts decay slowly, and so decay experiments take a long time. The quantity and range of reliable data are usually a limiting factor in the study of industrial catalyst decay kinetics. Whichever approach is adopted, the preferred model must be responsive to the key variables that affect the decay rate but no more complex than can be justified by the available data.38 The use of activity-time expressions or the equivalent independent decay kinetics is justified only when decay is proven to be independent of composition. Independent coking kinetics may be justified if reactants and products have similar, additive coking kinetics, but this must be supported by measurements of the axial activity and coke gradients. In ∼40% of the coking models found in the literature, the bed-average coke content was fitted without any evidence of a uniform coke profile. Any effects due to the coke distribution were effectively smoothed out in the data fitting. If the decay experiments provide insufficient data to determine a model, then computing power cannot correct this deficiency. Good practice includes parametric sensitivity analysis and careful model reduction. Would a simpler model fit the data almost as well? In one study, the denominator adsorption term was shown to be redundant because its value varied by
