Towards Predictive Simulations of Functional and Quantum Materials

PI Paul Kent, Oak Ridge National Laboratory
Co-PI Anouar Benali, Argonne National Laboratory
Olle Heinonen, Argonne National Laboratory
Jaron Krogel, Oak Ridge National Laboratory
Ye Luo, Argonne National Laboratory
Lubos Mitas, North Carolina State University
Miguel Morales, Lawrence Livermore National Laboratory
Eric Neuscamman, University of California, Berkeley
Fernando Reboredo, Oak Ridge National Laboratory
Luke Shulenburger, Sandia National Laboratories
Kent INCITE 2021
Project Summary

The goal of this project is the prediction and understanding of quantum-mechanical properties of materials that display novel properties including novel quantum phases.

Project Description

The goal of this project is the prediction and understanding of quantum-mechanical properties of materials that display novel properties including novel quantum phases. These materials are of outstanding fundamental scientific interest and present the potential for the development of new sensors and devices.

In all of the materials studied, small changes in composition, pressure, strain, doping, and applied field yield greatly altered properties, which is a challenge to simulation and modeling. This project therefore applies approaches based on Quantum Monte Carlo (QMC), as implemented in the open-source QMCPACK code. By directly solving the Schrödinger equation and by treating the electrons at a consistent highly-accurate many-body level, these methods can be applied to general elements and materials, while employing very few approximations.

Supported by the DOE BES Computational Materials Sciences Center for the Predictive Simulation of Functional Materials and core BES programs, this project operates alongside experimental collaborators to enable joint theory-experimental work.

Allocations