Independent Researcher, Toronto, Ontario M9B0E3, Canada.
Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States.
J Chem Theory Comput. 2023 Jun 27;19(12):3446-3459. doi: 10.1021/acs.jctc.3c00334. Epub 2023 May 30.
Polarizable force fields are pervasive in the fields of computational chemistry and biochemistry; however, their empirical or semiempirical nature gives them both weaknesses and strengths. Here, we have developed a hybrid water potential, named q-AQUA-pol, by combining our recent 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.
极化力场在计算化学和生物化学领域中无处不在;然而,它们的经验或半经验性质使它们既有弱点也有优点。在这里,我们通过将我们最近的 q-AQUA 势与 TTM3-F 水势相结合,开发了一种混合水势能,命名为 q-AQUA-pol。新的势能展示了前所未有的准确性,从气相团簇,例如水六聚体的八个低能异构体,到凝聚相,例如径向分布函数、自扩散系数、三重 OOO 分布和密度的温度依赖性。这代表了极化机器学习势能和计算建模领域的重大进展。