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Predictive Models for Transition Metal Catalyzed Organic Reactions

Due to limited mechanistic insights and the complexity of catalyst-substrate interactions, catalyst design and optimization in transition metal catalysis often rely on chemical intuition and experimental trial-and-error. I will discuss our recent efforts to utilize a streamlined computational approach to understand and predict the reactivity and selectivity of transition metal catalysts for various catalyst- and directing group-controlled reactions, including the functionalization of C-H/C-C bonds and olefins and polymerization reactions. Our approach is based on quantitative investigations of various steric, electronic, dispersion, and strain effects of the transition metal catalyst, the ligand, and the directing group. Computational models were developed to provide a straightforward way to identify the dominant factor controlling reactivity and selectivity. For catalyst-controlled reactions, we utilized the Ligand-Substrate Interaction Model to quantitatively analyze different types of through-bond and through-space interactions between the metal catalyst and the substrate. For reactions employing heteroatom-containing directing groups, we developed a Transition State Ring Strain Model to predict the ring-strain effects of the directing group. Finally, these theoretical insights are utilized to develop multivariate mathematical equations using simple physical organic chemistry parameters to rapidly predict the reactivity and selectivity of transition metal catalysts.

Speaker: Peng Liu, Univ. of Pittsburgh

Wednesday, 12/05/18


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Tan Hall

UC Berkeley
Room 775A
Berkeley, CA 94720