2 papers
cond-mat.mtrl-sci2026
Building a physics-aware AI ecosystem for solid-state hydrogen storage materials
Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu +66
Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evo…
physics.chem-ph2024
Self-learning path integral hybrid Monte Carlo with mixed ab initio and machine learning potentials for modeling nuclear quantum effects in water
Bo Thomsen, Yuki Nagai, Keita Kobayashi +2
The introduction of machine learned potentials (MLPs) has greatly expanded the space available for studying Nuclear Quantum Effects computationally with ab initio path integral (PI…