2 papers
physics.chem-ph2026
Monomeric machine learning potential for general covalent molecules: linear alkanes as an example
Xinze Li, Ruitao Ma, Chen Qu +2
Machine-learning potentials (MLPs) have become important tools for modern molecular simulations. However, developing models that simultaneously achieve high accuracy and high compu…
physics.chem-ph2024
Extending the atomic decomposition and many-body representation, a chemistry-motivated monomer-centered approach for machine learning potentials
Qi Yu, Ruitao Ma, Chen Qu +6
Most widely used machine learned (ML) potentials for condensed phase applications rely on many-body permutationally invariant polynomial (PIP) or atom-centered neural networks (NN)…