Theory and Design of Dinuclear Catalytic Reactions

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With support from the Chemical Catalysis program in the Division of Chemistry, Daniel Ess of Brigham Young University is focused upon advancing the theory and design of di-nuclear catalytic reactions in chemistry. Developing new catalysts is critical to discovering new, efficient chemical reactions. Historically, homogeneous catalysts use just one metal atom at the core of the catalyst. In contrast, dinuclear catalysts have two metal atoms at the core of the catalyst and have significant promise for new designs and modes of operation. Dinuclear catalysts also hold promise for speeding up historically slow/difficult chemical reactions where current single metal catalysts do not perform well. Currently, research scientists do not fully understand how dinuclear catalysts facilitate rapid reactions, or which dinuclear catalysts should be the target of synthesis for specific chemical transformations. In this project Dr. Daniel Ess will be using computational methods and theoretical analysis to understand mechanisms and selectivity of reactions catalyzed by such dinuclear metal systems. This work, interfaced tightly with experimental collaboration, will lead to the prediction and experimental discovery of new dinuclear catalysts and chemical reactions. This work will also provide training for undergraduate and graduate students as well as postdoctoral scholars at the interface between chemistry and computer science.Daniel Ess of Brigham Young University is using quantum-chemical methods and theoretical analyses to model and understand transition-metal heterodinuclear and homodinuclear catalysts for organic transformations. The dinuclear catalysts being investigated have direct bonding between two transition metals as the core of the catalyst. Reaction mechanisms will be investigated for C-H bond functionalization, C-O bond reduction, and dehydrogenation. Selectivity for hydrocarbon semi-hydrogenation, for cyclization reactions, and for stereoselective addition reactions will be the foci of these investigations. This work will be combining quantum-chemical methods and machine learning techniques to design new heterodinuclear catalysts. Undergraduate and graduate students and postdoctoral scholars will be trained in advanced computational techniques. Students and postdocs will interact directly with several experimental groups and learn how to apply computational chemistry techniques in an experimental environment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.