(5cf) A Computational Approach to Understanding the Structure-Performance Relationship of Systems Relevant for Catalysis

One of the main aims of the study of catalysis is to develop detailed models of catalytic processes at the atomic level. These atomic models provide a deeper understanding of the fundamental relationship between the structure and composition of a catalytic system and its performance (activity, selectivity, and lifetime) and have, therefore, the potential to enable scientists to design highly efficient catalytic materials, a priori, that can subsequently be synthesized.

Together with experimental scattering and spectroscopic techniques, computational methods have been used in the last decade to accurately model the structures of active sites, the diffusion processes to and from the active sites, and the mechanisms of the catalytic reactions. Despite the increasing availability of computational resources and improved algorithms, molecular modeling and simulation of large, complex systems at the atomic level remains a challenge and is currently limited to relatively simple, uniform catalytic materials. More complex systems that involve, for example, the interplay between multiple short-lived species on bimetallic nanoparticles ? a class of materials with great catalytic potential ? are still too intricate to model accurately from first principles. To enable simulations of complex systems that accurately reflect experimental observations, significant advances in modeling potential energy surfaces, statistical mechanical sampling, and multiscale modeling are necessary.

In recently completed work, I investigated the N₂O decomposition over iron zeolite catalysts. We were able to provide a complete analysis of this reaction relevant for the reduction of greenhouse gas emissions from nitric and adipic acid plants. Furthermore, we gained insights into the nature of the catalytically active sites and the effects of species such as H₂O and NO that have eluded experimentalists. In order to calculate the rates of the elementary processes occurring on the catalyst surface, new methods for finding transition states on high dimensional potential energy surfaces were developed that are included in the new version of Q-Chem 3.0, and that will be included in the next release of TURBOMOLE and VASP. In more recent work, I am developing multilevel methods, such as QM/MM methods, that combine quantum mechanics (QM) and molecular mechanics (MM), for simulating processes in solution and on nanoparticles. In my poster, I will outline how I plan to build on this experience to understand the structure-performance relationship of single-site catalysts, nanoparticles, and other systems relevant for catalysis.