most citedValidation Workflow for Machine Learning Interatomic Potentials for Complex Ceramics

13 citations · 20 across the 3 of their papers we have counts for

collaborators
Showing cond-mat.mes-hallShow all

1 paper · 1 filter

cond-mat.mes-hall2024

A Genetic Algorithm Trained Machine-Learned Interatomic Potential for the Silicon-Carbon System

Michael MacIsaac, Salil Bavdekar, Douglas Spearot +1

A linear regression-based machine learned interatomic potential (MLIP) was developed for the silicon-carbon system. The MLIP was predominantly trained on structures discovered thro…