Ten Guidelines for Catalyst Testing - ACS Symposium Series (ACS

Chapter 11

Ten Guidelines for Catalyst Testing Frits M . Dautzenberg

Downloaded by STANFORD UNIV GREEN LIBR on May 29, 2012 | http://pubs.acs.org Publication Date: October 3, 1989 | doi: 10.1021/bk-1989-0411.ch011

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This paper presents ten guidelines for an effective catalyst research program. The guidelines were devised specifically for scientists in vestigating catalysts in laboratory-scale equipment. These guidelines include identifying the objectives, planning an effective strategy, selecting the appropriate reactor, establishing an ideal flow pattern, ensuring isothermal conditions, diagnosing and mini mizing transport disguises, gathering meaningful data, assessing catalyst stability, following good experimental practice, and providing perspective on results. The guidelines represent years of experience rather than a review of the literature. They will help newcomers to the field operate effectively and will give ex perienced researchers new insights to current and future situations. An abundance of literature describes how experimental rate data and insights into catalytic chemistry help us understand reaction mechanisms, formulate improved catalysts, and generate kinetic models. However, this literature typically is oriented toward engineering and is beyond the needs of most scientists investigat ing catalysts in laboratory-scale equipment. This paper provides valuable advice on catalyst testing in a research set ting. It focuses on two key requirements for an effective catalyst research pro gram: (1) how to obtain reliable data and (2) how to do this with a well-conceived strategy. This paper also promotes an awareness of the impediments to reliable measurements of catalytic activity, the appropriate steps to overcome these inter ferences, and the special situations in which assistance of a reactor engineering specialist is needed. The overall emphasis is on catalyst testing rather than on reactor engineering. With these objectives in mind, the following " ten command ments" were formulated. I. Specify Objective It is important to define the objective of the envisioned catalyst testing program before starting the experiments. During preliminary screening, many catalysts are 0097-6156/89/0411-0099$06.25/0 © 1989 American Chemical Society

In Characterization and Catalyst Development; Bradley, S., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1989.

100

CHARACTERIZATION AND CATALYST DEVELOPMENT


rated in relatively simple reactors, and easily determined performance parameters are measured. Few candidate catalysts go beyond this stage. This preliminary catalyst screening is generally followed by determining the key parameters that influence the reaction. Subsequently, the candidate catalysts are compared in more detail. When a catalyst with practical potential is identified, further experimenta tion usually includes characterization of the reaction mechanism and kinetic meas urements. More careful experimentation and higher accuracy are increasingly important. Subsequendy, catalyst life tests may be required, preferably in a simu lated industrial environment, to determine the long-term catalyst behavior. This may necessitate optimization of reaction conditions and further catalyst improvements. Knowing how the catalyst will react in an industrial environment is required to assess how scale up will affect the catalyst performance. This informa tion also will optimize the industrial reactor design. Many times pilot plants are the only source for this information. These stages of a catalyst research and development program are usually sequential and are obviously subject to iteration. Because time and resource allocation usually increase with each iteration, it is beneficial to identify the specific objective, which will influence equipment selection, experimental strategy, and required accuracy.

H.

Use Effective Strategy

Well-designed, appropriate experimental strategies will greatly enhance the effec tiveness of a laboratory testing program. Statistically derived experimental strategies developed over recent decades provide the following benefits: More information per experiment Key variables isolated early Valid conclusions despite experimental uncertainty Built in procedures to check the validity of conclusions •

Interactions among variables detected Significant time savings

•

Organized collection and presentation of results

•

Up front estimate of required number of experiments

The recommended strategy depends on the available information and the objective of the catalyst testing program. In exploratory programs it is important to establish which of the many variables (e.g., temperature, pressure, pretreatment conditions, catalyst preparation method) will have the greatest influence on catalyst performance. Factorial designs are recommended for such situations (7). Beyond simply identifying the key variables, one usually wants to know quantita tively how the variables affect catalyst performance. The required mathematical relationships can be generated by regression methods (2). In other situations one may want to know what combination of values of the key variables leads to optimum performance. Optimization strategies can quickly lead to this result (3).



11.

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101

Ten Guidelines for Catalyst Testing

Table I compares results achieved when seven variables that may affect the performance of a particular catalyst were tested one-at-a-time with results from a statistical design (fractional factorial) approach. In this comparison, a shift in measured performance is assumed to be real if it represents at least twice the uncertainty of the measuring technique. The one-at-a-time strategy, still prevalent among many catalyst researchers, requires 48 experiments to determine with 95% confidence which variables significantly impact catalyst performance. Whereas, with the fractional factorial approach, this same information was obtained in only 16 experiments with a 98.5% confidence level. The fractional factorial approach also shows possible interactions among the variables; the classical one-at-a-time approach does not. Table I. Statistical Design versus One-Variable-at-a-Time Approach Fractional One-at-a-time factorial strategy design Number of variables

7

7

Experiments required

48

16

95%

98.5%

No

Yes

Confidence level Information about interactions

Note: Real effect is 2X experimental uncertainty Many catalyst researchers are unaware of the potential benefits of statisti cal design of experiments. Others have had unfortunate experiences with socalled designed experiments because they underestimated the influence of experimental uncertainties on the reliability of the conclusions. In both cases familiarity with the fundamentals of statistical inference in the experimentation strategy is beneficial (4). Statistically derived strategies can certainly offer many important benefits, although they obviously cannot replace creativity or sound technical judgment.

HI. Select Appropriate Reactor Selection of the laboratory reactor requires considerable attention. There is no such thing as a universal laboratory reactor. Nor should the laboratory reac tor necessarily be a reduced replica of the envisioned industrial reactor. Figure 1 illustrates this point for ammonia synthesis. The industrial reactor (5) makes effec tive use of the heat o f reaction, considering the non-isothermal behavior of the reaction. The reactor internals allow heat to exchange between reactants and products. The radial flow of reactants and products through the various catalyst beds minimizes the pressure drop. In the laboratory, intrinsic catalyst characteriza tion is done with an isothermally operated plug flow microreactor (6). Generating the desired information in a reliable and reproducible manner is a leading criterion in selecting a laboratory reactor. This is not a straightforward exercise, and many factors must be considered such as the purpose of the


102



experiment, the physical nature of the reaction system, the ease of construction and operation, cost efficiency, and the integrity and evaluation of the resulting data. Often the laboratory reactor must be capable of continuous, steady-state operation under conditions of isobaricity, isothermality, ideal flow, and without concentration gradients. These elements will be discussed in more detail later in this paper. For the reasons outlined above, continuously stirred tank reactors (CSTR) and plug flow reactors (PFRs) are usually preferred over batch, fluidized-bed, bubble column, and trickle-bed reactors. Batch reactors, although still popular in many laboratories, are not well suited for kinetic investigations. It is impossible to uncouple the main reaction kinetics from deactivation, and it is difficult to deter mine the actual reaction time. The complex hydrodynamics in fluidized-bed and bubble column reactors do not permit accurate assessment of intrinsic catalyst behavior. Expert assistance is required to interpret process conditions. Laboratoryscale trickle-bed reactors can be designed to compare catalysts. They are also suitable for life testing of catalyst samples. However, laboratory-scale trickle-bed reactors are generally not good tools for determining reaction kinetics or for characterizing highly active catalysts. A CSTR is preferred for laboratory catalyst testing. Operated properly, a CSTR offers the following attractive features: Gradientless operation • •

Simple mathematical treatment of the data Separation of reaction kinetics and deactivation parameters Uniform catalyst deactivation

The PFR is efficient for screening solid catalyst in a single fluid phase. It can also be used in later research stages to assess commercial criteria. Consider the evaluation of the ultimate commercial performance of a newly developed fixed-bed catalyst. The theory of similarity teaches that for the laboratory and the industrial reactor, the Damkohler number (NDa), the Sherwood number (Nsh), and the Thiele modulus ((])) need to be kept constant (Figure 2). As a result, the laboratory reactor must have the same length as the envisioned commercial reactor (7). In this case, scale up is done by increasing the diameter of the reactor. This example further illustrates that laboratory reactors are not necessarily small in size. IV. Establish Ideal Flow Pattern Continuous reactors (8n/8t = 0) are characterized by the nature of their flow pat tern, which lies between the ideal extremes of the plug flow and completely mixed patterns (Figure 3). These two patterns are called ideal because they enable reliable and straightforward treatment of data avoiding the radial and axial disper sion terms in the continuity equation (#). Analyzing data from other than an ideal flow pattern requires complicated mathematical treatment, if possible at all, and should therefore not be used for laboratory testing (9).



DAUTZENBERG

Industrial Ammonia Reactor

Laboratory Microreactor Reactant

Reactant

I


Catalyst Catalyst

Product

~ Product

Key Challenge: Accounting for the non-Isothermal behavior Figure 1. Comparison of a laboratory microreactor and envisioned industrial reactor for ammonia synthesis. Laboratory Prototype Reactor

Characteristic Dimensionless Numbers

Commercial Reactor

Da

Sh

Figure 2. Schematic of prototype tube. Completely Mixed:

Plug Flow:

0, c

m

R = Q

c

dc dV

Q R =Y

(

°1

c

' o)

Q, C! Q, q Any Other Flow Pattern:

D H

J _ i n , 3Qc =

V 3t

2

n U

ac

Q±jLtr 50 is usually acceptable. For fixed-bed reactors, L/dp > 50 is indeed a sufficient re quirement, provided a particle Reynolds number (NR ) is 10 or above. In laboratory experiments the particle Reynolds numbers, however, are usually much smaller, and Re < 0.1 is more the rule than the exception. The literature does not stress this point sufficiently, which has led to confusion and many mis conceptions. e

V. Ensure Isothermal Conditions In many laboratory situations, intrinsic kinetic parameters are obtained under isothermal conditions. This is extremely important because relatively small chan ges in temperature can affect reaction rates significantly. Figure 4 shows how much the reaction rate will change for a 3 °C deviation as function of the activa tion energy and the assumed operating temperature. Macrogradients in the reactor temperature may cause intrareactor gradients, which can cause deviations from isothermality (72). In addition to temperature gradients at the reactor level, temperature gradients (interphase gradients) can also occur at the boundary between the catalyst and the reactor fluid. With solid catalyzed reactions, such gradients may also occur within the catalyst particles. These gradients are called intraparticle gradients (Figure 5). Axial and radial gradients can be distinguished with respect to intrareactor temperature gradients. In fixed-bed reactors, axial temperature gradients always exist because of conversion. These gradients can be minimized by increasing the ratio of bed length to catalyst particle diameter, L/dp (see Table II). Radial temperature gradients probably cause unreliable data in plug flow reactors, which are attributable to the low effective thermal conductivity (13) of the catalyst bed. These intrareactor temperature gradients are nearly always more severe than inter phase temperature gradients, which are generally more severe than intraparticle temperature gradients. The intraparticle temperature gradients are inconsequential because the effective thermal conductivity of the catalyst is usually larger than that of the surrounding fluid. In the catalyst particle, heat transfer occurs mostly by conduction through the solid phase. The extent to which catalyst activity measurements are disturbed by in trareactor, interphase, and intraparticle effects of heat transport is assessed by evaluating experimental catalyst performance using the mathematical criteria in Table IH (72).


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105

Table II. Steps for Ensuring Plug Flow Operation in Laboratory Reactors

1. Determine the viscosity of the fluid medium at reactor conditions.


2. Calculate the superficial fluid velocity (u): 3. Calculate the particle Reynolds number:

N

u d_P E-

=

R

4. Calculate the Peclet number: N

-

P e

(0.034)

N

R C p

°'

5 3

(^j

(for liquid-phase operation)

0 23 / L \ N = (0.087) 5. Calculate NPe •

N

P e

R e

i^-j

^*

(for gas-phase operation)

N

N

p

r e

min

= 8n In — i — 1 -

X

6. Acceptable deviation from plug flow can be assumed if: N

p e

> N

p

e

.

7. The minimum L / d follows from: p

jjp > (235.3) N

~°'

R

e

p

~°'

5 3

n In f ~ ~

(for liquid-phase operation)

and

T~ > (92.0) N

R

2 3

n In "j—^— (for gas-phase operation)



106


Temperature (°C)

Figure 4. Deviation in reaction rate for a 3 °C deviation at a given activation energy and temperature.

Pore Structure (Intraparticle)

Figure 5. Reactor and catalyst gradients application to a heterogeneous catalyst.


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DAUTZENBERG


The mathematical criteria compare functions A and B of observable or measurable parameters. If A < B , it can be assumed that the relevant temperature gradient may cause a 10%).


Mathematical criteria aid in understanding what reactor system features can be manipulated to achieve better isothermal control. Based on this, the follow ing recommendations can help establish isothermal catalyst testing: •

Use CSTR if possible

•

Work at low conversion levels

•

Use small catalyst particles

•

Decrease bed voidage Select catalyst support with high thermal conductivity

•

Add feed diluent with high thermal conductivity (H2 and He above 500 K)

•

Apply high flow rates

VI. Diagnose and Minimize Transport Disguises In investigating heterogeneously catalyzed reactions, an important, early objec tive is to determine whether intrinsic catalyst properties have been measured. Heat or mass transfer effects, caused by intrareactor, interphase, or intraparticle gradients (see Figure 5), can disguise the results and lead to misinterpretations. Before accurate and intrinsic catalyst kinetic data can be established, these dis guises must be eliminated by adjusting the experimental conditions. In a well-stirred CSTR, intrareactor gradients will be absent, but inter phase and intraparticle gradients may be present. Conversely, in a fixed-bed PFR with small catalyst particles, intraparticle gradients may be eliminated, although intrareactor gradients still occur. The following experimental tests can be performed to determine whether a certain gradient is important (5). The tests are relatively simple and require no a priori assumptions or estimates of numerical values. In a flow system, the flow rate can be varied while the space velocity is kept constant (Figure 6). If the conversion remains constant, the in fluence of interphase and intrareactor effects may be assumed to be negli gible. A similar test can be done in a CSTR. In that case the absence of interphase and intrareactor effects can be assumed if the reaction rate is independent of the rate of agitation. •

Changing catalyst particle sizes can be used to test intraparticle effects (Figure 7). If there is no change of catalyst activity with change in par ticle size (assuming the exposed surface area of active catalyst is con stant), the catalyst is considered to be free of intraparticle gradients. Koros and Nowak (14) proposed an alternative but more complex test. The test is based on the proportionality of the reaction rate to the number


107


Table III. Criteria for Isothermal Operation Intrareactor frHl

v

k


2

R r

t

Ten Guidelines for Catalyst Testing - ACS Symposium Series (ACS

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