Density diversity in training data governs thermodynamic transferability of machine learning interatomic potentials

Minwoo Kim, Seungtae Kim, Je-Yeon Jung +2

Machine learning interatomic potentials (MLIPs) offer first-principles accuracy with reduced computational cost, but their transferability across different thermodynamic states rem…