Inorganic Chemistry Commons^™

Transition Metal Computational Catalysis: Mechanistic Approaches And Development Of Novel Performance Metrics, Brett Anthony Smith

Doctoral Dissertations

Computational catalysis is an ever-growing field, thanks in part to the incredible progression of computational power and the efficiency offered by our current methodologies. Additionally, the accuracy of computation and the emergence of new methods that can decompose energetics and sterics into quantitative descriptors has allowed for researchers to begin to identify important structure-function relationships that predict the properties of unexplored subspaces within the overall chemical space. Catalytic descriptors have been used frequently in data driven high-throughput computational screenings. With the use of machine learning, a large portion of the chemical space an be predicted in matter of minutes or …

Synthesizing Strong Donor Macrocyclic Tetracarbene Metal Complexes For Catalytic Aziridination, Steven Alan Cramer

Doctoral Dissertations

A small ringed macrocyclic tetracarbene ligand was developed due to the inherent ability of N-heterocyclic carbenes (NHCs) to stabilize high oxidation states of transition metals. This new strong donor ligand was prepared by first synthesizing an 18-atom ringed macrocyclic tetraimidazolium ligand precursor. The tetraimidazolium can be prepared by a two-step procedure. This ligand precursor was deprotonated to prepare a monomeric platinum tetracarbene complex.

A new iron macrocyclic tetra-carbene complex was synthesized by an in situ strong base deprotonation strategy of the ligand precursor. The iron tetracarbene complex was found to catalyze the aziridination of a wide array of functionalized aryl …