As one of the most widely employed types of chemical reactors within the chemical engineering industry, heterogeneous catalytic reactors have the versatility and efficiency to facilitate crucial chemical processes. For heterogeneous catalytic reactors, catalysts exist in a different phase than the reactants. Linking the macro-scale transport phenomena and the micro-scale reaction kinetics in the mesoscale is crucial to reactor design, optimization, and scale-up. Mesoscale simulations can assist in the study of heterogeneous catalytic reactors, understanding of the empirical knowledge and lowering the cost of reactor development. For this purpose, this dissertation presents 3 new tools developed for Stochastic Rotation Dynamics (SRD), a mesoscale method particularly well suited for problems involving both microscale effects on surfaces and transport phenomena in fluids: real-time temperature measurement and simulation, surface reactions and interactions simulation and surface reactions simulation in complex random geometry...@en

In heterogeneous catalysis, reactivity and selectivity are not only influenced by chemical processes occurring on catalytic surfaces but also by physical transport phenomena in the bulk fluid and fluid near the reactive surfaces. Because these processes take place at a large range of time and length scales, it is a challenge to model catalytic reactors, especially when dealing with complex surface reactions that cannot be reduced to simple mean-field boundary conditions. As a particle-based mesoscale method, Stochastic Rotation Dynamics (SRD) is well suited for studying problems that include both microscale effects on surfaces and transport phenomena in fluids. In this work, we demonstrate how to simulate heterogeneous catalytic reactors by coupling an SRD fluid with a catalytic surface on which complex surface reactions are explicitly modeled. We provide a theoretical background for modeling different stages of heterogeneous surface reactions. After validating the simulation method for surface reactions with mean-field assumptions, we apply the method to non-mean-field reactions in which surface species interact with each other through a Monte Carlo scheme, leading to island formation on the catalytic surface. We show the potential of the method by simulating a more complex three-step reaction mechanism with reactant dissociation.

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Many physical and chemical processes involve energy change with rates that depend sensitively on local temperature. Important examples include heterogeneously catalyzed reactions and activated desorption. Because of the multiscale nature of such systems, it is desirable to connect the macroscopic world of continuous hydrodynamic and temperature fields to mesoscopic particle-based simulations with discrete particle events. In this work we show how to achieve real-time measurement of the local temperature in stochastic rotation dynamics (SRD), a mesoscale method particularly well suited for problems involving hydrodynamic flows with thermal fluctuations. We employ ensemble averaging to achieve local temperature measurement in dynamically changing environments. After validation by heat diffusion between two isothermal plates, heating of walls by a hot strip, and by temperature programed desorption, we apply the method to a case of a model flow reactor with temperature-sensitive heterogeneously catalyzed reactions on solid spherical catalysts. In this model, adsorption, chemical reactions, and desorption are explicitly tracked on the catalyst surface. This work opens the door for future projects where SRD is used to couple hydrodynamic flows and thermal fluctuations to solids with complex temperature-dependent surface mechanisms.

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