Argonne maintains a wide-ranging science and technology portfolio that seeks to address complex challenges in interdisciplinary and innovative ways. Below is a list of all articles, highlights, profiles, projects, and organizations related specifically to computational materials science.
Shashi specializes in high-fidelity multiphysics/multiscale simulations and reduced-order modeling in multi-disciplinary areas of science and engineering using supercomputers.
Our research covers wide areas of condensed matter physics and quantum materials, including superconductivity, magnetism, low-dimensional systems, topological matter, nonequilibrium and driven systems, and quantum dynamics.
Machine learning, a field focused on training computers to recognize patterns in data and make new predictions, is helping doctors more accurately diagnose diseases and stock analysts forecast the rise and fall of financial markets.