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most citedExtrapolation of Machine-Learning Interatomic Potentials for Organic and Polymeric Systems

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physics.chem-ph2026

A Generalized Approach for Incorporating Geometry and Directionality into Coarse-Grained Machine-Learned Potentials

Arthur Y. Lin, Tejas Dahiya, Rose K. Cersonsky

Machine-learned interatomic potentials have enabled highly accurate atomistic simulations, but extending these capabilities to coarse-grained systems remains challenging due to the…