A machine-learning-potential framework achieves an optimal balance of accuracy and efficiency through monomeric decomposition. Systematic evaluations highlight its potential in large-scale simulations of complex molecular systems.
- Qi Yu
- Ruitao Ma
- Joel M. Bowman