In Search of a More Perfect Forcefield: Considerations and Strategies for Parameterizing Complex Interatomic Potentials for Molecular Dynamics

Molecular Dynamics (MD) simulations are an increasingly vital tool to understand molecular processes in a variety of material systems across mechanical, materials, and biological engineering. MD simulations require parameterized interatomic forcefields that capture complex interatomic interactions in materials. However, forcefield parameterization is a non-trivial global optimization problem involving quantification of forcefield variables in large-dimensional search spaces.<br/><br/>This talk will discuss currently used strategies to parameterize reactive and non-reactive interatomic potentials and will identify opportunities for improving these strategies through newly developed algorithms and software for performing multi-objective and global optimization, as well as schemes inspired by AI and ML training. Using EZFF, a Python package for parameterization of several types of interatomic forcefields using single- and multi-objective optimization techniques, I will describe a meta-analysis of the performance of forcefields for complex multi-phase materials generated using different strategies such as force-matching, energy-fitting and direct parameterization against dynamical properties. Approaches for parameterization of new forcefields against sparse ground truth data from experiments or expensive simulations will also be analyzed.