QMC Simulations Database for Predictive Modeling and Theory

PI Jeongnim Kim, Oak Ridge National Laboratory
Researchers at Argonne, Purdue, and Oak Ridge are studying the properties of catalytic nanoparticles on graphene supports using Quantum Monte Carlo methods.
Project Description

The project will involve quantum Monte Carlo (QMC) studies in heterogeneous catalysis of transition metal nanoparticles, phase transitions, properties of materials under pressure, and strongly correlated materials. These research directions share a common need for predictive simulations where the relevant energy scales are small enough to be beyond the reach of other methods and where correlations, van der Waals interactions, or localization of d or f states play critical roles. These systems have significant scientific and community impact by providing accurate predictions for energy-related materials and predictions of fundamental material properties that other methods are unable to reliably provide.

The project will both provide direct answers to fundamental materials science questions and establish benchmark levels of accuracy that will, in turn, provide targets for future developments in related electronic structure approaches.

Allocations