Takuma Ikeda

Adaptive multiscale simulations have long faced a dilemma: when identical solvent molecules switch between resolutions, nonphysical transition forces appear, forcing a choice between distorted solvation structure and broken Hamiltonian conservation. The Integrated Molecular Model (IMM) uses a multilayer perceptron that takes only the multiscale weight functions as input to learn and cancel those transition forces, yielding artifact-free solvation structures in bulk water, aqueous K+, Na+, NH4+, Ca2+, Cl– and H3O+ systems while conserving energy over long NVE runs. The correction force costs about 1.8% of the time per step, and a model trained on K+ transfers to Na+ and NH4+ without retraining.

Adaptive multiscale simulations have long faced a dilemma: when identical solvent molecules switch between resolutions, nonphysical transition forces appear, forcing a choice between distorted solvation structure and broken Hamiltonian conservation. The Integrated Molecular Model (IMM) uses a multilayer perceptron that takes only the multiscale weight functions as input to learn and cancel those transition forces, yielding artifact-free solvation structures in bulk water, aqueous K+, Na+, NH4+, Ca2+, Cl– and H3O+ systems while conserving energy over long NVE runs. The correction force costs about 1.8% of the time per step, and a model trained on K+ transfers to Na+ and NH4+ without retraining.