10 citations · 30 across the 18 of their papers we have counts for
18 papers
Diagnosing Latent Energy Decomposition in Machine-Learning Interatomic Potentials via Interacting Quantum Atoms
Kohei Shimamura, Ken-ichi Nomura
Machine-learning interatomic potentials (MLIPs) can reproduce potential energies and forces accurately, but their internal energy allocation is often difficult to interpret. E3D-IQ…
Benchmarking Universal Machine Learning Force Fields for Molecular Dynamics of Lunar Regolith Minerals
Ziyu Huang, Ken-ichi Nomura
Universal machine-learning interatomic potentials provide a promising route for accelerating molecular dynamics simulations of materials, but their transferability to lunar regolit…
EquiFiLM: Charge-Conditioned Equivariant Force Fields via Feature-wise Linear Modulation
Samuel Sahel-Schackis, Ken-ichi Nomura, Aiichiro Nakano +2
Foundation machine learning force fields (MLFFs) such as MACE-MP-0 and UMA cover broad chemical space at near density functional theory (DFT) accuracy. However, they assume equilib…
Toward Exascale AI for Science: A Scalable AI Skill for Autonomous Microkinetics Discovery
Ken-ichi Nomura, William Dawson, Nabankur Dasgupta +4
We present a scalable AI-driven framework that advances autonomous scientific discovery by combining agentic workflow automation, high-performance computing, and scientific surroga…
Multiscale light-matter dynamics in quantum materials: from electrons to topological superlattices
Taufeq Mohammed Razakh, Thomas Linker, Ye Luo +12
Light-matter dynamics in topological quantum materials enables ultralow-power, ultrafast devices. A challenge is simulating multiple field and particle equations for light, electro…
Beyond Scaling: Chemical Intuition as Emergent Ability of Universal Machine Learning Interatomic Potentials
Shinnosuke Hattori, Kohei Shimamura, Aiichiro Nakano +3
Machine Learning Interatomic Potentials (MLIPs) have successfully demonstrated scaling behavior, i.e. the power-law improvement in training performance, however the emergence of no…