Shotgun crystal structure prediction using machine-learned formation energies

arXiv:2305.02158v3 Announce Type: replace-cross
Abstract: Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface defined on the space of the atomic configurations. Generally, this requires repeated first-principles energy calculations that are impractical for large systems, such as those containing more than 30 atoms in the unit cell. Here, we have made significant progress in solving the crystal structure prediction problem with a simple but powerful machine-learning workflow; …

abstract arxiv cond-mat.mtrl-sci energy global machine physics.comp-ph prediction space stat.ml surface systems type