2021 Annual Meeting
(551h) A New Approach to Predicting Saturated Liquid Viscosity from MD Simulations for Transferability and Accuracy
This work shows recent success in developing a novel force field for molecular simulation that is parameterized to simultaneously reproduce saturated liquid densities and viscosities. The big goal is to create a technique that is both transferrable to compounds outside the training set and can predict viscosity at better than 10% accuracy across a range of temperatures. The presentation begin with an explanation of the basics of calculating viscosity from molecular simulation and the issues that must be addressed surrounding both the method and the model. The results of a novel parameterization scheme will then be given, and a comparison to other viscosity prediction methods will be shown. The presentation will also discuss why historical approaches often have difficulty because the parameterization focuses on the attractive portion of the model while spending less effort on the repulsive part. Taken as a whole, the work demonstrates that accurate viscosity prediction is possible via MD when force fields are parameterized for transport properties as well as thermodynamic properties, that the molecular-level phenomena giving rise to viscosity are not intuitive, and that there is reason to hope for better predictions of the property in the near future.