equivariant neural networks 1foundation models 1machine-learned interatomic potentials 1materials discovery 1thermal conductivity prediction 1
From the 1 of 2 linked papers with an AI index.
2 papers
physics.comp-ph2026
Fast and Accurate Foundation Models for Equivariant Machine-Learned Interatomic Potentials
Seán R. Kavanagh, Chuin Wei Tan, Menghang Wang +12
The paper presents fast and accurate equivariant machine‑learned interatomic potentials (NequIP and Allegro) as foundation models that scale to ultra‑large datasets while maintaini…
cond-mat.mtrl-sci2025
Exploring Charge Density Waves in two-dimensional NbSe2 with Machine Learning
Norma Rivano, Francesco Libbi, Chuin Wei Tan +8
Niobium diselenide (NbSe) has garnered significant attention due to the coexistence of superconductivity and charge density waves (CDWs) down to the monolayer limit. However, r…