2 papers
cond-mat.mtrl-sci2021
Assessing the Accuracy of Machine Learning Thermodynamic Perturbation Theory: Density Functional Theory and Beyond
Basile Herzog, Mauricio Chagas da Silva, Bastien Casier +5
Machine learning thermodynamic perturbation theory (MLPT) is a promising approach to compute finite temperature properties when the goal is to compare several different levels of a…
cond-mat.mtrl-sci2020
Self-consistent potential correction for charged periodic systems
Mauricio Chagas da Silva, Michael Lorke, Bálint Aradi +5
Supercell models are often used to calculate the electronic structure of local perturbations from the ideal periodicity in the bulk or on the surface of a crystal or in wires. When…