Catalyst micro kinetics

As described above, the activity of a catalyst can be measured by mounting it in a plug flow reactor and measuring its intrinsic reactivity outside equilibrium, with well-defined gas mixtures and temperatures. This makes it possible to obtain data that can be compared with micro-kinetic modeling. A common problem with such experiments materializes when the rate becomes high. Operating dose to the limit of zero conversion can be achieved by diluting the catalyst with support material. 

Finally, the constructed micro-kinetic model must of course be tested against measurements performed with real catalysts. Figure 7.23 shows a plot of the calculated output from the reactor against experimental values. Apparently, the micro-kinetic model describes the situation very well. This does not prove that the model is correct since models based on another series of elementary steps might also work. 

A full analysis of the rate expression reveals that all data on the Cu(lOO) single crystal are modeled very well, as shown in Fig. 8.10. Even more important is that the model also describes data obtained on a real catalyst measured under considerably different conditions reasonably well, indicating that the micro-kinetic model captures the most important features of the methanol synthesis (Fig. 8.11). 

Figure S.11. Comparison between the predictions of a micro-kinetic model and measurements on a Cu(lOO) model catalyst with a real methanol synthesis catalyst. The full line represents the ideal match between model and experiment. [Adapted from P.B. Rasmussen, P.M. Holmblad, T. Askgaard,...

The contribution of different crystal planes to the overall surface area of the particle can thus be calculated and is shown in Fig. 8.12(b). The results have been included in a dynamical micro-kinetic model of the methanol synthesis, yielding a better description of kinetic measurements on working catalysts [C.V. Ovesen, B.S. Clausen, J. Schiotz, P. Stoltze, H. Topsoe and J.K. Norskov, J. Catal. 168 (1997) 133]. 

The multi-functionality of metal oxides1,13 is one of the key aspects which allow realizing selectively on metal oxide catalysts complex multi-step transformations, such as w-butane or n-pentane selective oxidation.14,15 This multi-functionality of metal oxides is also the key aspect to implement a new sustainable industrial chemical production.16 The challenge to realize complex multi-step reactions over solid catalysts and ideally achieve 100% selectivity requires an understanding of the surface micro-kinetic and the relationship with the multi-functionality of the catalytic surface.17 However, the control of the catalyst multi-functionality requires the ability also to control their nano-architecture, e.g. the spatial arrangement of the active sites around the first centre of chemisorption of the incoming molecule.1... 

A general issue in these studies is that the preparation method is quite different from ones used to prepare real catalysts to be tested under practical conditions. This is an important issue, because there is the need to link the micro-kinetic and surface mechanism studies to the catalytic behaviour under real conditions, and to use the knowledge generated by the fundamental investigations to prepare industrially relevant catalysts. 

If one can understand what the basic parameters of the reactants and the surface are that determine the reaction dynamics (activation barriers etc.) then given a micro-kinetic model one has a knowledge of the factors determining the catalytic activity of the catalyst. 

If the aim is to explore the mechanism of the reaction and understand which are the important parameters of the catalyst determining the activity, then a micro-kinetic model is needed. A micro-kinetic model is based on a detailed mechanism and independent information about the rates of the elementary steps involved and the stability of the intermediates. The micro-kinetic model is the synthesis of all the basic knowledge about a reaction over a given catalyst. 

The inhibition by hydrogen was obviously more pronounced in the micro channels. Without hydrogen in the feed, the reaction rate was on average 34% higher for the coated catalysts. The kinetic expression described the reaction rate experimentally observed with an error of < 15% for the packed bed and < 20% for the micro channels (see Figure 2.6) [24]. 

Figure 25 Micro-kinetic simulation of the CO + NO reaction on a Pd/MgO model catalyst, (a) Steady state production of C02 as a function temperature at Pco = 5 x 10 s Torr and various NO pressures, (b) Steady state coverage of NO, CO and O as a function of sample temperature for Pco = 7 no = 5 x 1CT8 Torr (from Ref. [167]).

Unfortunately, these requirements have not yet fully been met for any catalytic reaction, although for some simple catalytic reactions reasonable approaches are known. Such reactions are the oxidation of CO over a supported Rh catalyst [46,47], ammonia synthesis over iron [48, 49], and the HCN synthesis over a Pt gauze catalyst. More recently Wolf [50] carried out a micro-kinetic analysis of the primary reaction steps in the oxidative coupling of methane and also related the rate... 

The above thermochemical values were used to fill the heterogeneous module of the kinetic scheme for the OCM reaction over a model Li/MgO catalyst with corresponding kinetic parameters (see Table III). In combination with a scheme of homogeneous methane oxidation, this set of reactions forms the desired micro-kinetic description. It allowed us to re-consider specific features of the OCM process and to obtain some unexpected results. 

Of course, such accounting for mass-transfer is an oversimplification of real processes taking place during alkane oxidation over real catalysts. Additional studies are required to estimate the possibility to integrate a detailed microchemical (and micro-kinetic) description with methods capable of advanced accounting of mass-transfer on the inter- and intra-particle level and in the bulk of reactor (see, for instance, Couwenberg, 1994 Hoebink et al, 1994). 

A detailed computational model was developed for several different iimovative designs for the preferential carbon monoxide (CO) oxidation reactor using a kinetic mechanism and reaction sequence derived from a micro-kinetic model and literature data for the specific adsorption coefficients and kinetic parameters for a platinum-based catalyst. 

Surface segregation of Pd in Pd—Rh catalysts suppresses NOx reduction [61]. De Sarkar and Khanra studied the segregation difference between Pd—Rh and Pt—Rh nanoparticles, and the influence of sulfur in fuel on CO oxidation and NO. They used Monte-Carlo (MC) simulation to predict the surface composition of PtsoRhso and PdsoRhso particles (2406 atoms for 4nm particles). TTiey used a micro-kinetic model to compare the activities of both soHds for reactions of CO -i- O2, CO -I- NO and CO -1- NO -1- O2, and found that Pt and Pd segregate to the particles surface, especially in the Pd catalyst, which is clearly better for CO oxidation, while Pt—Rh is a better catalyst for NO reduction. For both reactions, sulfur poisons the Pd—Rh catalyst more than the Pt—Rh catalyst [62]. 

This paper discusses research efforts towards the prediction of hydrocarbon product distribution for the Fischer-Tropsch synthesis (FTS) on a cobalt-based catalyst using a micro-kinetic model taken fiom the literature. In the first part of the study, a MATLAB code has been developed which uses the Genetic Algorithm Toolbox to estimate parameter values for the kinetic model. The second part of the study describes an ongoing experimental campaign to validate the model predictions of the fixed-bed reactor FTS product distribution in both conventional (gas phase) and non-conventional (near-critical and supercritical phase) reaction media. 

Basically, the micro kinetic approach explores the detailed chemistry of the reaction. On the other hand, the empirical models are based on the experimental results and are typically expressed in the Arrhenius model and provide an easy and computationally lighter way to predict the rate of reaction. The main disadvantage is the fact that the adjusted model cannot be extrapolated to different composition and types of catalysts. 

A micro-kinetic analysis [415] showed that the activation energy increases by 34 kJ/mol on the alkali-promoted catalyst. At the same time, alkali causes the pre-exponential factor to increase by a factor of 15. This could be explained by potassium blocking the highly active step site. 

The heterogenicity of catalyst surfaces makes problems complicated. If the kinetic data were obtained in a narrow range of experimental conditions, only Langmuir kinetics could be applied. If using the wide range of experimental conditions, micro-kinetic model may involve non-Langmuir effect of surface coverage state. 

In order to verify that the fixed bed and the micro-channel reactor are equivalent concerning chemical conversion, an irreversible first-order reaction A —) B with kinetic constant was considered. For simplicity, the reaction was assumed to occur at the channel surface or at the surface of the catalyst pellets, respectively. Diffusive mass transfer to the surface of the catalyst pellets was described by a correlation given by Villermaux [115]. 

Smallness of micro-flow components safety gains tool for kinetics evaluation process development for large-scale processes polymerization combinatorial catalyst screening hydrogen via reforming [218],... 

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