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cond-mat.mtrl-sci2026
Benchmarking empirical and machine-learned interatomic potentials using phase diagram predictions for Lead
Tom Hellyar, Pascal T. Salzbrenner, Peter I. C. Cooke +3
We compare the predicted phase behaviour of lead (Pb) using three different interatomic potential models, including an embedded atom method (EAM), a modified embedded atom method (…
cond-mat.mtrl-sci2023
Neural-Network Force Field Backed Nested Sampling: Study of the Silicon p-T Phase Diagram
N. Unglert, J. Carrete, L. B. Pártay +1
Nested sampling is a promising method for calculating phase diagrams of materials, however, the computational cost limits its applicability if ab-initio accuracy is required. In th…