Project Details
Meeting the challenge of computational discovery, fundamental understanding, and design of real functional materials with unique physical properties ultimately relies on the availability of sufficiently reliable and predictive computational methods. Achieving the desired predictiveness for general materials remains highly challenging, particularly where strong electron correlations, spin-orbit interactions, and van der Waals interactions couple with the atomic structure of the materials. At the same time, these interactions can result in novel physical properties that are highly desired for energy applications. The mission to the Center for Predictive Simulation of Functional Materials is therefore to provide a leap forward in state-of-the-art methods that can make highly accurate and reliable quantum-mechanics-based predictions in these classes of materials.
To achieve this goal, the Center focuses on advances in Quantum Monte Carlo (QMC) techniques, their implementation in the open-source QMCPACK code, and the workflow software and supporting data required for broad utilization. Validation and initial scientific application of these new methods will be to materials and properties where existing theoretical and computational methods are not predictive, including quantum materials such as challenging layered magnets and layered materials that are proposed to exhibit novel quantum phases. QMCPACK has been expressly designed to run performance portably from laptops up to exascale machines such as Frontier at OLCF and Aurora at ALCF. The combination of improved QMC techniques and advanced computational implementation is expected to enable application to new condensed matter systems as well as enable higher-throughput uses for machine learning and artificial-intelligence based applications.
The team consists of condensed matter theory, materials, and high-performance computing staff, professors, students and postdoctoral research associates at Argonne, Sandia, and Oak Ridge National Laboratories, and North Carolina State and Brown Universities.
