Abstract:

I will describe my group’s use of DFT static and dynamics calculations combined with automation tools, ligand libraries, and machine learning to design new and more selective organometallic catalysts. I will emphasize our strategies and tools to design Cr-based ethylene oligomerization catalysts and Fe-oxo based alkane C-H functionalization catalysts.

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.