10 citations · 30 across the 18 of their papers we have counts for
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cond-mat.mtrl-sci2023
Molecular Autonomous Pathfinder using Deep Reinforcement Learning
Ken-ichi Nomura, Ankit Mishra, Tian Sang +3
Diffusion in solids is a slow process that dictates rate-limiting processes in key chemical reactions. Unlike crystalline solids that offer well-defined diffusion pathways, the lac…
cs.DC2023★ 3 cited
Allegro-Legato: Scalable, Fast, and Robust Neural-Network Quantum Molecular Dynamics via Sharpness-Aware Minimization
Hikaru Ibayashi, Taufeq Mohammed Razakh, Liqiu Yang +8
Neural-network quantum molecular dynamics (NNQMD) simulations based on machine learning are revolutionizing atomistic simulations of materials by providing quantum-mechanical accur…