Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

Kohn–Sham Density Functional Theory (KSDFT) is the most widely used electronic structure
method in chemistry, physics, and materials science, with thousands of calculations cited …

Orbital-free density functional theory (OFDFT) is both grounded in quantum physics and
suitable for direct simulation of thousands of atoms. This article describes the application of …

We present the results of the first Charged-Particle Transport Coefficient Code Comparison
Workshop, which was held in Albuquerque, NM October 4–6, 2016. In this first workshop …

Energy functionals serve as the basis for different models and methods in quantum and
classical many-particle physics. Arguably, one of the most successful and widely used …

We have performed density functional theory (DFT) based calculations for aluminum in
extreme conditions of both pressure and temperature, up to five times compressed ambient …

We present simulations using finite-temperature density-functional-theory molecular
dynamics to calculate the dynamic electrical conductivity in warm dense aluminum. The …

We perform first-principles path integral Monte Carlo (PIMC) and density functional theory
molecular dynamics (DFT-MD) calculations to explore warm dense matter states of …

Orbital-free density functional theory constitutes a computationally highly effective tool for
modeling electronic structures of systems ranging from room-temperature materials to warm …

We develop a framework for on-the-fly machine learned force field (MLFF) molecular
dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF …