Optimal catalyst distribution

Vayenas, C. G. and S. Pavlou. 1987a. Optimal catalyst distribution and generalized effectiveness factors in pellets single reactions with arbitrary kinetics. Chem. Eng. Sci. 42(11) 2633-2645. 

As discussed in this volume, the use of membrane reactors (Bernstein, et oL), monoliths (Hickman and Schmidt), optimized catalyst distribution in pellets (Gavriilidis and Varma), and supercritical conditions (Azzam and Lee) are examples of engineering developments that may provide improvements over existing processes. 

The effects of non-uniform distribution of the catalytic material within the support in the performance of catalyst pellets started receiving attention in the late 60 s (cf 1-4). These, as well as later studies, both theoretical and experimental, demonstrated that non-uniformly distributed catalysts can offer superior conversion, selectivity, durability, and thermal sensitivity characteristics over those wherein the activity is uniform. Work in this area has been reviewed by Gavriilidis et al. (5). Recently, Wu et al. (6) showed that for any catalyst performance index (i.e. conversion, selectivity or yield) and for the most general case of an arbitrary number of reactions, following arbitrary kinetics, occurring in a non-isothermal pellet, with finite external mass and heat transfer resistances, the optimal catalyst distribution remains a Dirac-delta function. 

Vayenas, C. G., and Pavlou, S., Optimal Catalyst Distribution for Selectivity Maximization in Pellets. Paper No. 72d, AIChE Annual Meeting, Washington, D.C., Nov. 27-Dec. 2, 1988. 

The performance indexes, which define an optimal catalyst distribution, include effectiveness, selectivity, yield and deactivation rate. The key parameters, affecting the choice of the optimal catalyst profile, are the reaction kinetics, the transport resistances, and the production cost of the catalyst. An extensive review of the theoretical and experimental developments in this area is available [20]. Two typical examples to demonstrate the importance of an appropriate distribution of the active components are now described. 

Yeung et al. [1994] extended the studies to a general case of a bed of catalyst pellets on the feed side of a membrane reactor where the membrane is catalytically inert for an arbitrary number of reactions with arbitrary kinetics under nonisothermal conditions. Their conclusions are similar to those for the case of pellets in a fixed bed reactor [Baratti et al., 1993]. It appears that the presence of a catalytically inert membrane and a permeate su-eam do not affect the nature of the optimal catalyst distribution but may... 

Besides total conversion, other reaction performance index may benefit from optimizing the catalyst distribution and location. Examples are product purity on the feed or p>ermeate side and product molar Row rate on the feed or permeate side. Yeung et al. [1994] have also investigated these aspects and provided comparisons among IMRCF, FBR and catalytic membrane reactor (CMR) in Figure 9.8. It is apparent that the various reaction performance indices call for different optimal catalyst distributions. 

The optimal catalyst distribution problem was studied in an adiabatic reactor (Ogunye and Ray, 197la,b). The optimal initial distribution of catalyst activity along the axis of a tubular fixed-bed reactor was examined for a class of reactivation-deactivation problems by Gryaert and Crowe (1976). A general set of simultaneous reactions was considered, quasi steady state approximation was used, and the decay of the catalyst expressed as a function of temperature, concentration and catalyst activity. The influence of various initial catalyst activity distributions upon the reactor performance was also considered. 

T. Bacaros, S. Bebelis, S. Pavlou and C.G. Vayenas, Optimal catalyst distribution in pellets with shell progressive poisoning the case of linear kinetics, in Catalyst Deactivation 1987 (B. Delmon and G.F. Forment, Eds.), pp. 459-468,1987. 

Fill the marked comers with the types of catalyst pellet given below and give reasons for the choices. The shaded part of the pellets is inert. Refer to Becker and Wei (1977). For optimal catalyst distribution, see Varghese and Wolf (1980) and Dadyburjor (1982). 

Variables It is possible to identify a large number of variables that influence the design and performance of a chemical reactor with heat transfer, from the vessel size and type catalyst distribution among the beds catalyst type, size, and porosity to the geometry of the heat-transfer surface, such as tube diameter, length, pitch, and so on. Experience has shown, however, that the reactor temperature, and often also the pressure, are the primary variables feed compositions and velocities are of secondary importance and the geometric characteristics of the catalyst and heat-exchange provisions are tertiary factors. Tertiary factors are usually set by standard plant practice. Many of the major optimization studies cited by Westerterp et al. (1984), for instance, are devoted to reactor temperature as a means of optimization. 

Jain, Biegler, and Jhon [126] optimized Pt distribution along the width of the CL and found that a significant improvement in current density could be obtained by placing higher amounts of Pt adjacent to the catalyst layer/membrane interface. 

The optimal distribution of silver catalyst in a-Al203 pellets is investigated experimentally for the ethylene epoxidation reaction network, using a novel single-pellet reactor. Previous theoretical work suggests that a Dirac-delta type distribution of the catalyst is optimal. This distribution is approximated in practice by a step-distribution of narrow width. The effect of the location and width of the active layer on the conversion of ethylene and the selectivity to ethylene oxide, for various ethylene feed concentrations and reaction temperatures, is discussed. The results clearly demonstrate that for optimum selectivity, the silver catalyst should be placed in a thin layer at the external surface of the pellet. 

The characterization of the flow in existing DPF materials has been assessed by experiments and macroscopic continuum flow in porous media approaches. However, when it comes to material design it is essential to employ flow simulation techniques in geometrically realistic representations of DPF porous media. Some first applications were introduced in Konstandopoulos (2003) and Muntean et al. (2003) and this line of research is especially important for the development of new filter materials, the optimization of catalyst deposition inside the porous wall and for the design of gradient-functional filter microstructures where multiple functionalities in terms of particle separation and catalyst distribution (for combined gas and particle emission control) can be exploited. 

Over the past 10 years a multitude of new techniques has been developed to permit characterization of catalyst surfaces on the atomic scale. Low-energy electron diffraction (LEED) can determine the atomic surface structure of the topmost layer of the clean catalyst or of the adsorbed intermediate (7). Auger electron spectroscopy (2) (AES) and other electron spectroscopy techniques (X-ray photoelectron, ultraviolet photoelectron, electron loss spectroscopies, etc.) can be used to determine the chemical composition of the surface with the sensitivity of 1% of a monolayer (approximately 1013 atoms/cm2). In addition to qualitative and quantitative chemical analysis of the surface layer, electron spectroscopy can also be utilized to determine the valency of surface atoms and the nature of the surface chemical bond. These are static techniques, but by using a suitable apparatus, which will be described later, one can monitor the atomic structure and composition during catalytic reactions at low pressures (< 10-4 Torr). As a result, we can determine reaction rates and product distributions in catalytic surface reactions as a function of surface structure and surface chemical composition. These relations permit the exploration of the mechanistic details of catalysis on the molecular level to optimize catalyst preparation and to build new catalyst systems by employing the knowledge gained. 

Feed source may also have a substantial effect on the distribution parameter (Tamm et al., 1981). Given the complexity of crude oil with reference to residuum properties, it is not surprising that differences in metal distribution parameters are observed. This finding suggests that optimal catalyst properties may vary with the residuum source. Galliasso et al. (1985) have compared the HDM kinetics of porphyrins and nonporphyrin compounds in both resins and asphaltenes. The individual... 

To illustrate the functionality of the system a validation library was prepared and introduced into the reactor system. With the goal of achieving an optimal fluid distribution with a minimal pressure drop over the 96 reactor channels we used multichannel ceramic bodies ( miniliths ) as supports, which are impregnated with the corresponding catalyst precursor solutions in an automatic manner (for suitable technical solutions see Section 2). At each of the 96 reactor positions, a candidate material modified by impregnation is available for testing. The shadowed scheme... 

The choice of reactor configuration depends on the properties of the reaction system. For example, bioconversions for which the homogeneous catalyst distribution is particularly important are optimally performed in a reactor with the biocatalyst compartmentalized by the membrane in the reaction vessel. The membrane is used to retain large components, such as the enzyme and the substrate while allowing small molecules (e.g., the reaction product) to pass through. For more labile molecules, immobilization may increase the thermal, pH and storage stability of biocatalysts. 

The performance of adsorptive (and indeed almost all multifunctional) reactors benefits from an expedient nonuniform distribution and integration of the functionalities at various levels. Simply combining given proportions of catalyst and adsorbent in a fixed-bed reactor seldom realizes the full potential available [52]. The objective may be to maximize utilization of adsorbent capacity or to optimize catalyst productivity. Although these aims need not be mutually exclusive, they often give rise to different strategies. 

Figure 6.16 displays the temperature profile and liquid-phase molar fractions for cumene and DIPB. It may be observed that the temperature is practically constant over the reactive sections with a first plateau at 200 °C and a second one at 210 °C. The top temperature is at 198 °C while the bottom temperature climbs to 242 °C. The explanation may be found in the variation of concentrations for cumene and DIPB in the liquid phase. The maximum reaction rate takes place on the stages where propylene is injected. The cumene concentration increases rapidly and reaches a flat trend corresponding to the exhaustion of the propylene in liquid phase. It may be seen that the amount of DIPB increases considerably in the second reaction zone. This variation is very different from that with a cocurrent PFR. The above variations suggest that the productivity could be improved by providing several side-stream injections and/or optimizing the distribution of catalyst activity. 

The catalyst distribution on stages may be also seen as an optimization variable, but the effect on productivity is rather small. The real advantage comes from a... 

The substrate was usual 1.1 mm glass with sputtered aluminium layer. Ni was used as a catalyst. For optimization of cathode surface topography, three types of samples were prepared, with different catalyst distribution on the substrate. Catalyst layer in the first sample was uniform sputtered Ni layer. In the second and the third samples, the catalyst sputtering was produced through screens with 1 mm h 50 pm holes correspondingly. The distance between holes compared with the twice island diameter. The total area of each cathode sample was about 0.5 cm2. Cathodes are shown on Fig. 1. 

Figure 22. Influence of activity profiles on the temperature profile of a strongly exothermic reaction. A) Catalyst with 66% activity in the front section and 100% activity in the back [37] B) Linear (broken line) and optimal catalyst activity distribution (full line) for limiting the maximum temperature to 370 °C (simulation result) C) Experimental verification of B [38].

The dedicated scanning transmission electron microscope (STEM) is an integral tool for characterizing catalysts because of its unique ability to image and analyze nano-sized volumes. This information is valuable in optimizing catalyst formulations and determining causes for reduced catalyst performance. For many commercial catalysts direct correlations between structural features of metal crystallites and catalytic performance are not attainable. When these instances occur, determination of elemental distribution may be the only information available. In this paper we will discuss some of the techniques employed and limitations associated with characterizing commercial catalysts. 

Catalyst attached to membrane pore surface. The final distribution of the catalyst in the membrane pores can significantly impact the reactor performance. The optimal form of the catalyst distribution for maximizing conversion was studied mathematically by Keller et al. [1984]. They determined that the optimal distribution of the catalyst concentration is of the Dirac delta function. 

When the Dirac delta distribution is placed closer to the permeate side (i.e., a subsurface step distribution) of an CMR, the total conversion is actually lower than that with a uniform catalyst distribution (Figure 9.7). For a performance index other than the total conversion (such as product purity or product molar flow rate), the optimal distribution of the catalyst concentration can be rather complex even for reversible first-order reactions as displayed in Figure 9.8. 

Preparation of membranes with pores having non-uniform catalyst distributions. It has been indicated that special, non-uniform catalyst distributions inside the membrane pores offer optimal reaction performance indices such as the total conversion, product purity and product molar flow rate. Specifically, surface step distributions near the pore mouths or subsurface step distributions inside the membrane pore channels are preferred. 

The performance of OCFS as mass transfer devices is heavily dependent on the quality of the distribution of the gas and liquid phases across the column upon entry to the packed section—irrespective of whether its function is purely rectification/stripping or chemical conversion also. Optimal liquid distribution is, however, of additional importance in catalytic distillation, in ensuring contacting of reactants with the catalyst. 

The above modeling study showed therefore the importance of having a proper knowledge of the pore texture and catalyst distribution of the catalytic filter, since they can seriously affect its performance. This suggests, in line with Ref. 40, the need of a proper characterization of the porous structure of the catalytic filters, concerning pore connectivity, pore size distribution, presence of deadend pores, etc., since each of these features might play a primary role in reactor performance. On the basis of such characterization work, valuable information could be drawn in order to choose or optimize the preparation routes. 

However, approximate treatment is possible. Ikeda and Tashiro (19) report an optimization of catalytic reactions in fluid beds. They And that the maximum yield of the intermediate product decreases, and that the optimum contact time increases for first-order consecutive and parallel reaction systems if contact efficiency in the reactor decreases. They also showed the most economical equilibrium activity and the optimal size distribution of catalyst. 

A. Bninovska, M. Morbidelli and P. Brunovskyf Optimal catalyst pellet activity distribution for deactivating systemsf Chen gng. Sci-, A5 (1990) 917 - 925 ... 

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