McGreal, Meghan2022-08-292022-08-292021-06https://hdl.handle.net/11299/241433University of Minnesota Ph.D. dissertation. June 2021. Major: Chemistry. Advisor: Jason Goodpaster. 1 computer file (PDF); xviii, 151 pages.Computational chemistry is a useful tool for studying the aspects of chemistry that cannot be wholly studied in a laboratory setting, such as mechanisms, electronic structure, reaction barriers, and other various chemical and physical properties. In this dissertation, computational chemistry methods, specifically Density Functional Theory (DFT), is utilized to study complex catalytic systems. These systems include transition-metal based metalloenzymes and molecular catalysts that were studied utilizing electronic structure methods. Chapters 2, 3, and 4 focus on elucidation of catalysis, structural features, function, and other various properties of the [NiFe]-hydrogenase enzyme system. Specifically, the mechanism of catalysis was studied, appropriate models for the study of this bimetallic enzyme active site were determined (Chapter 2), the effect of mutation of highly conserved residues were analyzed (Chapter 3), and the influence biomimetic-inspired changes to the active site were assessed (Chapter 4). Chapter 5 focuses on elucidating the structure and function of the non-heme Fe chlorination enzyme, SyrB2, in collaboration with the Bhagi-Damodaran Group. Chapter 6 is a study of titanium-catalyzed nitrene transfer of diazenes to isocyanides for carbodiimide synthesis in collaboration with the Tonks Group. Finally, Chapter 7 is computational determination of the chemical hardness of various anions, as well as the effect of stability of anion impact, selectivity and affinity for Gd-containing complexes in collaboration with the Pierre Group.enCatalysisDFTEnzymeHalogenaseHydrogenaseThesis or Dissertation