Kinetic modelling of heterogeneous catalytic systems

Abstract

The importance of heterogeneous catalysis in modern life is evidenced by the fact that numerous products and technologies routinely used nowadays involve catalysts in their synthesis or function. The discovery of catalytic materials is, however, a non-trivial procedure, requiring tedious trial-and-error experimentation. First-principles-based kinetic modelling methods have recently emerged as a promising way to understand catalytic function and aid in materials discovery. In particular, kinetic Monte Carlo (KMC) simulation is increasingly becoming more popular, as it can integrate several sources of complexity encountered in catalytic systems, and has already been used to successfully unravel the underlying physics of several systems of interest. After a short discussion of the different scales involved in catalysis, we summarize the theory behind KMC simulation, and present the latest KMC computational implementations in the field. Early achievements that transformed the way we think about catalysts are subsequently reviewed in connection to latest studies of realistic systems, in an attempt to highlight how the field has evolved over the last few decades. Present challenges and future directions and opportunities in computational catalysis are finally discussed.

Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

“…8 The MME is derived from first principles and its transition probabilities or rate constants are computed with quantum chemical methods. 7,9 General MKM models result by applying a system-size expansion, thereby focusing on the behavior of the master equation at the thermodynamic limit of very large lattices. In this limit, stochastic fluctuations become negligible and one can formulate ordinary differential equations (ODEs) that describe the temporal evolution of the average surface coverage.…”

Deterministic and Monte Carlo methods for simulation of plasma‐surface interactions

“…Despite their popularity, deterministic models are not always accurate because of a number of simplifying assumption on which they rely. For instance, the assumption of a homogeneous distribution of surface species totally neglects spatial correlations or configuration‐dependent interactions that may occur in real systems . Furthermore, the deterministic approach fails when the fluctuations of the number of particles become important (e.g., interstellar dust grains that receive extremely low fluxes of reactive species).…”

Influence of reduction temperature on the formation of intermetallic Pd2Ga phase and its catalytic activity in CO2 hydrogenation to methanol

“…In CO 2 hydrogenation reaction to methanol, the selectivity of the desired product is highly sensitive to the catalyst structure . Different phases (with different Miller indices) in a metal‐loaded catalyst are a function of various parameters including catalyst preparation method, reduction temperature, and molar ratio of metals in bimetallic .…”