Exascale Simulations of Quantum Materials

PI Paul Kent, Oak Ridge National Laboratory
Co-PI Anouar Benali, Argonne National Laboratory
Panchapakesan Ganesh, Oak Ridge National Laboratory
Jaron Krogel, Oak Ridge National Laboratory
Ye Luo, Argonne National Laboratory
Lubos Mitas, North Carolina State University Fernando
A. Reboredo, Oak Ridge National Laboratory
Brenda Rubenstein, Brown University
Luke Shulenburger, Sandia National Laboratories
QMCPACK: Electron spin density of cobalt-doped silver nickel oxide delafossite

Researchers are using the QMCPACK code to accurately predict complex materials properties, such as the electron spin density of cobalt-doped silver nickel oxide delafossite depicted in this image. Image by ALCF Visualization and Data Analytics Team.

Project Summary

This INCITE project helps to meet the challenges of reducing energy, realizing new technologies, and identifying the optimum materials for specific applications.

Project Description

This project is focused on being able to reliably predict, understand, and realize desired phenomena in specific, real materials. Advances are critical to help meet the challenges of reducing energy, realizing new technologies, and identifying the optimum materials for specific applications. 

The team’s focus is on materials and properties where commonly used electronic structure methods are thought to be inaccurate due to their inherent approximations and where insight from benchmark accuracy calculations is needed, such as two-dimensional nanomaterials and “quantum materials”. Calculations are performed using the open-source QMCPACK code that implements Quantum Monte Carlo (QMC) algorithms. These methods are highly accurate and avoid the majority of problems of standard electronic structure methods, but at the trade-off of considerable additional computational cost.

Allocations