通讯：通过外推 Mayer 采样蒙特卡罗模拟来预测维里系数和化学转变。
Communication: Predicting virial coefficients and alchemical transformations by extrapolating Mayer-sampling Monte Carlo simulations.
机构信息
Chemical Informatics Research Group, Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8380, USA.
Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA.
出版信息
J Chem Phys. 2017 Dec 21;147(23):231102. doi: 10.1063/1.5016165.
Virial coefficients are predicted over a large range of both temperatures and model parameter values (i.e., alchemical transformation) from an individual Mayer-sampling Monte Carlo simulation by statistical mechanical extrapolation with minimal increase in computational cost. With this extrapolation method, a Mayer-sampling Monte Carlo simulation of the SPC/E (extended simple point charge) water model quantitatively predicted the second virial coefficient as a continuous function spanning over four orders of magnitude in value and over three orders of magnitude in temperature with less than a 2% deviation. In addition, the same simulation predicted the second virial coefficient if the site charges were scaled by a constant factor, from an increase of 40% down to zero charge. This method is also shown to perform well for the third virial coefficient and the exponential parameter for a Lennard-Jones fluid.
通过统计力学外推，从单个 Mayer 采样蒙特卡罗模拟中，在计算成本增加最小的情况下，预测了大范围的温度和模型参数值（即化学转变）下的 Virial 系数。通过这种外推方法，对 SPC/E（扩展简单点电荷）水模型的 Mayer 采样蒙特卡罗模拟定量预测了第二 Virial 系数，该系数是跨越四个数量级的数值和三个数量级的温度的连续函数，偏差小于 2%。此外，如果将站点电荷按常数因子缩放，该模拟还可以预测第二 Virial 系数，从增加 40%到零电荷。该方法还可用于 Lennard-Jones 流体的第三 Virial 系数和指数参数，效果良好。
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