2 papers
cond-mat.mtrl-sci2024
Polyvalent Machine-Learned Potential for Cobalt: from Bulk to Nanoparticles
Marthe Bideault, Jérôme Creuze, Ryoji Asahi +1
We present the development and applications of a quadratic Spectral Neighbor Analysis Potential (q-SNAP) for ferromagnetic cobalt. Trained on Density Functional Theory calculations…
physics.chem-ph2024
A dual-cutoff machine-learned potential for condensed organic systems obtained via uncertainty-guided active learning
Leonid Kahle, Benoit Minisini, Tai Bui +4
Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the first-p…