7 citations · 7 across the 3 of their papers we have counts for
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cond-mat.mtrl-sci2026
PFP/MM: A Hybrid Approach Combining a Universal Neural Network Potential with Classical Force Fields for Large-Scale Reactive Simulations
Yu Miyazaki, Atsuhiro Tomita, Akihide Hayashi +3
Universal machine-learning interatomic potentials (uMLIPs) enable reactive molecular simulations with near-DFT accuracy, yet applying them efficiently to large, realistic condensed…
cond-mat.mtrl-sci2025
Ready-to-Use Polymerization Simulations Combining Universal Machine Learning Interatomic Potential with Time-Dependent Bond Boosting for Polymer and Interface Design
Hodaka Mori, Shunsuke Tonogai, Yu Miyazaki +2
Although polymerization and curing reactions govern the performance of advanced materials, their simulation remains challenging owing to the need for accurate, transferable potenti…