About the Seminar
I will describe my group’s use of quantum-chemical calculations and machine learning to decode key physical principles for organometallic catalyst design and analysis of nonstatistical reaction dynamics. For catalyst design, I will discuss our efforts to design Cr-based ethylene trimerization and tetramerization catalysts that have been experimentally realized (Chem. Sci. 2020, 9665). For reaction dynamics, I will highlight successes and struggles to identify the physical origins of reaction selectivity through analysis of direct dynamics trajectories of nonstatistical organic reactions (Phys. Chem. Chem. Phys. 2021, 23, 12309 and J. Phys. Chem. A 2020, 124, 4813).
About the Speaker
Daniel H. Ess is a professor in the Department of Chemistry and Biochemistry at BYU (https://esslab.byu.edu/). He received his B.S. from BYU and Ph.D. from UCLA followed by postdoctoral work at Scripps-Florida, Caltech, and UNC Chapel Hill. His group uses and develops computational chemistry tools to discover reaction mechanisms, reactivity and selectivity principles, and design catalysts. His research ranges from applied catalyst prediction and realization with industrial collaborators to fundamental insights from direct dynamics studies. He also carries out experimental gas-phase light alkane C-H functionalization reactions. He directs a summer NSF REU program (https://reu.chem.byu.edu/). He is the creator and director of the BYU Chem Camp program (https://chemcamp.byu.edu/). For education, he creates interactive learning tools, such as the “iORA” application that displays reactive organic trajectories and is available on the iPhone App Store.