Aiming for Chemical Accuracy in Ground-state Density Functional Theory

University Of California-Irvine, Irvine CA

Investigators

Abstract

With support from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry, Professor Kieron Burke of the University of California, Irvine will endeavor to improve ground state density functional theory (DFT). Each year, more than 50,000 scientific papers use DFT to predict the properties of molecules and solids, and to design new pharmaceutical drugs and materials. About 1/3 of US supercomputer use is devoted to this task. But such calculations are limited due to poor performance of approximations. The aim of this work is to develop a new mathematical framework that has the promise of breakthroughs in both accuracy and speed of DFT calculations. Improvements in speed or accuracy of DFT calculations on the scale of this proposal would transform both the nature and capabilities of most DFT applications. Contrbuting to education and outreach, graduate and undergraduate students involved in this project will be trained to acquire high level knowledge of DFT, in a diverse and multi-national research group. A self-guided online course in Machine Learning in the Physical Sciences, developed by the Burke group and already available to all UC-Irvine students and faculty, will be made available to the public. This proposal combines semiclassical methods (expansions in powers of h, Planck's constant), density­-corrected DFT for separating energy errors from density-driven errors, and machine learning for finding approximate functionals from data. The aim is to go from proof-of-principle to approximate density functionals that can be applied to routine calculations. If successful, the research being undertaken under this award has the potential (a) to transform the basic starting point (generalized gradient approximations) of all DFT calculations into a new form; (b) to unite the functionals used in materials with those in chemistry; (c) to produce chemical accuracy for strong bonds at equilibrium, and (d) to apply to the non-interacting kinetic energy, and so impact orbital-free DFT. In short, success here would likely contribute to all fields currently using DFT calculations, and thus, the potential to achieve far-reaching broader scientific impact. 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.