Prof. Heather Kulik, Stanford University
810 South Clinton Street
May 9, 2012
Predictive and Fast: New First-Principles Tools for Transition Metal Catalysis
Abstract:
Rational, computational design is a promising pathway to the development of novel catalysts and materials, but the effectiveness of this design strategy is dependent upon the predictive accuracy and computational cost of the methods employed. Density functional theory (DFT) is a widely-employed computational approach for determining the electronic structure of molecules and solids, but standard DFT suffers from a critical error known as self-interaction that causes electrons to over-delocalize and yields erroneous descriptions of geometry and energetics. I will introduce a method in which I augment standard DFT with a Hubbard U term that ameliorates this error, particularly for the accurate and predictive description of transition-metal catalysis. This so-called DFT+U approach reduces errors in the ordering of electronic states of small molecules and paradigmatic catalytic reactions by over an order of magnitude. Importantly, with little additional overhead, the additional U term is calculated self-consistently on each system considered and is thus not a fitting parameter. The application of DFT+U to larger-scale systems including self-assembled monolayers of porphyrins on transition-metal surfaces, relevant to molecular spintronics, and on the activity of a non-heme iron halogenase, relevant to natural product synthesis, will also be discussed. Finally, if time permits, a brief segue into how quantum chemical methods on newer architectures can permit the ab initio study of systems several orders of magnitude larger in size will be discussed.
Date posted
Jun 17, 2019
Date updated
Jun 17, 2019