2 papers
physics.chem-ph2026
Explicit, Machine-Learned Two-Body Potentials for Molecular Simulations
Kham Lek Chaton, Eric D. Boittier, Mike Devereux +1
A new pairwise hybrid machine-learning/molecular mechanics (ML/MM) potential is introduced that is conceived for application to large, heterogeneous condensed-phase systems. The Ph…
physics.chem-ph2025
Cluster Models for Next-Generation, Machine-Learning-Based Energy Functions for Molecular Simulations
JingChun Wang, Meenu Upadhyay, Eric D. Boittier +7
Energy functions for pure and heterogenous systems are one of the backbones for molecular simulation of condensed phase systems. With the advent of machine learned potential energy…