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Application of Computational Methods to Supported Metal–Oxide Catalysis

Enhancing the design of supported metal–oxide catalysts, featuring metal particles dispersed on an oxide support, is essential for optimizing the performance of numerous industrial chemical processes. Advances in computational chemistry over the last few decades have had a great impact on design strategies for obtaining active, selective, and stable catalysts. This chapter outlines computational approaches for modeling metal–oxide catalytic systems at the atomic level, and reviews pertinent studies that exemplify these methods. Examples are chosen to emphasize both quantum-based methods [utilizing density functional theory (DFT) and ab initio thermodynamics] and classical force-field methods (utilizing the ReaxFF empirical potential). We discuss studies that use DFT to evaluate the relative energies of metal–oxide surface structures, studies that extend the formalism of DFT to non-zero temperature and pressure via ab initio thermodynamics, and finally studies that use the COMB and ReaxFF empirical force-fields in MD and MC simulations to investigate system dynamics and structure at large scales. Reviewing the application of these methods will provide the reader with a general understanding of how computational methods can be applied to atomistic studies of supported metal–oxide catalysts.

Print publication date: 02 Dec 2013
Copyright year: 2014
Print ISBN: 978-1-84973-451-6
PDF eISBN: 978-1-84973-490-5
From the book series:
Catalysis Series