Even though atomistic and CG models have been used to simulate liquid nanodroplets
in vapor, very few rigorous studies of the liquid-liquid interface structure are available,
and most of them are limited to planar interfaces. In this work, we evaluate several
existing force fields (FF)s, including two atomistic and three CG FFs, with respect to
modeling the interface structure and thermodynamic properties of the water-hexane
interface. Both atomistic FFs are able to quantitatively reproduce the interfacial
tension and the coexisting densities of the experimentally-observed planar interface.
We use the atomistic FFs to model water droplets in hexane and use these simulations
to test the CG FFs. We found that the tested CG FFs cannot reproduce the interfacial
tensions of planar and/or curved interfaces. Finally, we propose a new approach
for learning coarse-grained (CG) potentials within the CG SDK (Shinoda-DeVane-
Klein) FF framework from atomistic simulation data. We demonstrate that the new
potential significantly improves the prediction of both the interfacial tension and
structure of water-hexane planar and curved interfaces.
Revised: September 29, 2020 |
Published: August 24, 2020
Citation
Gao P., X. Yang, and A.M. Tartakovsky. 2020.Learning Coarse-Grained Potentials for Binary Fluids.Journal of Chemical Information and Modeling 60, no. 8:3731-3745.PNNL-SA-143761.doi:10.1021/acs.jcim.0c00337