Department of Chemical Engineering, University of California at Santa Barbara, California 93106, USA.
J Chem Phys. 2013 Sep 7;139(9):094107. doi: 10.1063/1.4819472.
To what extent can a "bottom-up" mesoscale fluid model developed through systematic coarse-graining techniques recover the physical properties of a molecular scale system? In a previous paper [C.-C. Fu, P. M. Kulkarni, M. S. Shell, and L. G. Leal, J. Chem. Phys. 137, 164106 (2012)], we addressed this question for thermodynamic properties through the development of coarse-grained (CG) fluid models using modified iterative Boltzmann inversion methods that reproduce correct pair structure and pressure. In the present work we focus on the dynamic behavior. Unlike the radial distribution function and the pressure, dynamical properties such as the self-diffusion coefficient and viscosity in a CG model cannot be matched during coarse-graining by modifying the pair interaction. Instead, removed degrees of freedom require a modification of the equations of motion to simulate their implicit effects on dynamics. A simple but approximate approach is to introduce a friction coefficient, γ, and random forces for the remaining degrees of freedom, in which case γ becomes an additional parameter in the coarse-grained model that can be tuned. We consider the non-Galilean-invariant Langevin and the Galilean-invariant dissipative particle dynamics (DPD) thermostats with CG systems in which we can systematically tune the fraction φ of removed degrees of freedom. Between these two choices, only DPD allows both the viscosity and diffusivity to match a reference Lennard-Jones liquid with a single value of γ for each degree of coarse-graining φ. This friction constant is robust to the pressure correction imposed on the effective CG potential, increases approximately linearly with φ, and also depends on the interaction cutoff length, rcut, of the pair interaction potential. Importantly, we show that the diffusion constant and viscosity are constrained by a simple scaling law that leads to a specific choice of DPD friction coefficient for a given degree of coarse-graining. Moreover, we find that the pair interaction distance cutoffs used for DPD random and dissipative forces should be considered separately from that of the conservative interaction potential.
从多大程度上,通过系统的粗粒化技术发展起来的“自下而上”介观流体模型可以恢复分子尺度系统的物理性质?在之前的一篇论文中[C.-C. Fu、P. M. Kulkarni、M. S. Shell 和 L. G. Leal,J. Chem. Phys. 137, 164106 (2012)],我们通过使用修改后的迭代玻尔兹曼反演方法开发粗粒化(CG)流体模型来解决这个问题,该方法可以重现正确的对结构和压力。在本工作中,我们关注的是动态行为。与径向分布函数和压力不同,在 CG 模型中,扩散系数和粘度等动力学性质不能通过修改对相互作用在粗粒化过程中进行匹配。相反,去除的自由度需要修改运动方程来模拟它们对动力学的隐含影响。一种简单但近似的方法是为剩余自由度引入摩擦系数γ和随机力,在这种情况下,γ成为 CG 模型中的一个附加参数,可以进行调整。我们考虑非伽利略不变的 Langevin 和伽利略不变的耗散粒子动力学(DPD)恒温器与 CG 系统,我们可以系统地调整去除自由度的分数φ。在这两种选择之间,只有 DPD 允许粘度和扩散系数与单个γ值匹配参考 Lennard-Jones 液体,每个粗粒化φ值都有一个γ值。这个摩擦常数对施加在有效 CG 势能上的压力校正具有鲁棒性,大约与φ呈线性关系,并且还取决于对相互作用势的截断长度 rcut。重要的是,我们表明扩散常数和粘度受到一个简单的标度律的约束,对于给定的粗粒化程度,这会导致 DPD 摩擦系数的特定选择。此外,我们发现 DPD 随机和耗散力使用的对相互作用距离截断应该与保守相互作用势能的截断分开考虑。