Abstract
Polarizable force fields are pervasive in the fields of computational chemistry and
biochemistry; however, their empirical or semi-empirical nature gives them both weaknesses
and strengths. Here, we have developed a hybrid water potential, named q-AQUA-pol, by combining our recent ab initio q-AQUA potential with the TTM3-F water potential. The new potential demonstrates unprecedented accuracy ranging from gas-phase clusters, e.g., the eight low-lying isomers of the water hexamer, to the condensed
phase, e.g., radial distribution functions, the self-diffusion coefficient, triplet OOO distribution, and the temperature dependence of the density. This represents a significant advancement in the field of polarizable machine learning potential and computational modeling.
Supplementary materials
Title
OO radial distribution function, time dependent properties
Description
Effects of many-body corrections on the OO radial distribution function, representative plots
of the time dependence of the the density of liquid water in NPT simulations and the mean
square displacement for classical MD and PIMD simulations
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