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Grand canonical Monte Carlo simulations of vapor-liquid equilibria using a bias potential from an analytic equation of state

机译:利用状态分析方程中的偏置电势对气液平衡进行经典的蒙特卡洛模拟

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This article introduces an efficient technique for the calculation of vapor-liquid equilibria of fluids. Umbrella Sampling Monte Carlo simulations in the grand canonical ensemble were conducted for various types of molecules. In Umbrella Sampling, a weight function is used for allowing the simulation to reach unlikely states in the phase space. In the present case this weight function, that allows the system to overcome the energetic barrier between a vapor and liquid phase, was determined by a trivialized Density Functional Theory (DFT) using the PC-SAFT equation of state. The implementation presented here makes use of a multicanonical ensemble approach to divide the space of fluctuating particle number N into various subsystems. The a priori estimate of the weight function from the analytic DFT allows the parallelization of the calculation, which significantly reduces the computation time. In addition, it is shown that the analytic equation of state can be used to substitute sampling the dense liquid phase, where the sampling of insertion and deletion moves become demanding.
机译:本文介绍了一种有效的技术来计算流体的汽液平衡。对各种类型的分子进行了大正则合奏中的伞采样蒙特卡罗模拟。在“伞式采样”中,权重函数用于允许模拟在相空间中达到不可能的状态。在当前情况下,该权重函数使系统能够克服气相和液相之间的能量屏障,这是通过使用PC-SAFT状态方程的平凡密度泛函理论(DFT)确定的。这里介绍的实现使用多规范集成方法将波动粒子数N的空间划分为多个子系统。通过分析DFT对权重函数进行先验估计可以并行化计算,从而显着减少了计算时间。另外,表明状态分析方程可以用来代替对稠密液相的采样,在该稠密液相中,插入和缺失移动的采样变得要求很高。

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