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Semi-bottom-up coarse graining of water based on microscopic simulations

机译:基于微观模拟的水的自下而上的半粗粒度

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The generalized dissipative particle dynamics (DPD) equation derived from the generalized Langevin equation under Markovian approximations is used to simulate coarse-grained (CG) water cells. The mean force and the friction coefficients in the radial and transverse directions needed for DPD equation are obtained directly from the all atomistic molecular dynamics (AAMD) simulations. But the dissipative friction forces are overestimated in the Markovian approximation, which results in wrong dynamic properties for the CG water in the DPD simulations. To account for the non-Markovian dynamics, a rescaling factor is introduced to the friction coefficients. The value of the factor is estimated by matching the diffusivity of water. With this semi-bottom-up mapping method, the radial distribution function, the diffusion constant, and the viscosity of the coarse-grained water system computed with DPD simulations are all in good agreement with AAMD results. It bridges the microscopic level and mesoscopic level with consistent length and time scales.
机译:在马尔可夫近似下,从广义Langevin方程派生的广义耗散粒子动力学(DPD)方程用于模拟粗粒度(CG)水单元。直接从所有原子分子动力学(AAMD)模拟中获得DPD方程所需的径向和横向平均力和摩擦系数。但是,在马尔可夫近似中高估了耗散摩擦力,这导致了DPD模拟中CG水的动态特性错误。为了解决非马尔可夫动力学问题,在摩擦系数中引入了比例缩放因子。通过匹配水的扩散率来估算因子的值。使用这种从下至上的映射方法,通过DPD模拟计算得到的粗粒水系统的径向分布函数,扩散常数和粘度都与AAMD结果完全吻合。它以一致的长度和时间尺度在微观层次和介观层次之间架起了桥梁。

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