Challenges in developing an extremely accurate many-body force field

Our group has been working to develop a physics-motivated, generalizable model fit only to quantum chemical data that reproduces experimental values of condensed phase properties across a wide range of conditions. Developing such a model is challenging and requires better physical models and higher accuracy quantum chemical reference data than are typically used when developing force fields for molecular dynamics simulations. I will describe some of our recent work that leverages machine learning ideas to generate high-accuracy quantum chemical reference data for the fitting of two-body and many-body models. I will also outline some theoretical and practical challenges in modeling many-body interactions and show a few preliminary results on small molecules of biochemical interest.