Author

M. Fernández-Pendás

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Preprint Sep 2026

Benchmarking Machine-Learning Interatomic Potentials for Dynamical Stability in Inorganic Semiconductor Nanocrystals: A CdSe Case Study

Machine-learning interatomic potentials (MLIPs) enable nanosecond-scale atomistic simulations of inorganic semiconductor nanocrystals, but low errors on held-out configurations do not necessarily guarantee stable molecular dynamics. We benchmark five graph-neural-network MLIPs, SchNet, PaiNN, NequIP, Allegro and MACE,...

Muhmmad Usman, M. Suleymanova, Zain Ul Abideen et al. · 0 citations