COMPUTATIONAL APPROACHES FOR MODELING AND UNDERSTANDING REACTIVITY IN METAL-ORGANIC FRAMEWORKS AND METAL SURFACES

Abstract

This dissertation focuses on computational techniques for modeling and understanding catalysis, particularly in surface/MOF reactions. The first chapter introduces basic concepts of catalysis, while the second chapter summarizes the computational approaches used throughout the dissertation. The third chapter presents a computational study of proton-coupled electron transfer reactions in metal-organic frameworks to facilitate an understanding of catalytic descriptors. This work highlights the use of computational techniques to gain atomistic insight into the redox chemistry of two metal-organic frameworks: Ce-MOF-808 and Ti-MIL-125. Key questions to be addressed include: Can we use MOFs to mimic metal oxide species and obtain thermodynamic descriptors of their reactivity? How do proton topologies of secondary building units affect the thermodynamics of PCET reactions? The fourth chapter focuses on the implementation and use of an electrostatic QM/MM embedding scheme for modeling MOF reactivity. It treats MOFs as reticular frameworks instead of clusters and allows for the inclusion of electrostatic interactions in the framework environment with minimal added computational cost compared to cluster models. Questions that we plan to address there include: How do different force fields/charges/QM/MM boundary schemes affect MOF modeling? How does the inclusion of electrostatic embedding affect the predicted MOF reactivity? How does the retention of lattice structure affect the thermodynamics of MOF reactions compared to cluster models? The fifth and final chapter employs contemporary energy decomposition analysis to understand linear scaling relations, which have been instrumental in the field of heterogeneous catalysis. While this chapter is not directly related to MOFs, the energy decomposition approach in Chapter 5 is readily applicable to MOF chemistry, particularly within the context of cluster modeling in Chapter 3 as well as the QM/MM modeling outlined in Chapter 4. The main questions are: Do ALMO-EDA energy terms follow similar linear scaling trends? Does ALMO-EDA provide an orbital picture that corroborates the d-band model, which rationalizes the difference in adsorbate binding across different metals?