Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA.
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA.
J Chem Phys. 2018 Jun 7;148(21):214105. doi: 10.1063/1.5020321.
Coarse-grained (CG) molecular dynamics (MD) simulations have become popular for investigating systems on multiple length and time scales ranging from atomistic to mesoscales. In CGMD, several atoms are mapped onto a single CG bead and the effective interactions between CG beads are determined. Iterative coarse-graining methods, such as iterative Boltzmann inversion (IBI), are computationally expensive and can have convergence issues. In this paper, we present a direct and computationally efficient theoretical procedure for coarse-graining based on the Ornstein-Zernike (OZ) and hypernetted chain (HNC) integral equation theory. We demonstrate the OZ-HNC-based CG method by coarse-graining a bulk water system, a water-methanol mixture system, and an electrolyte system. We show that the accuracy of the CG potentials obtained from the OZ-HNC-based coarse-graining is comparable to iterative systematic coarse-graining methods. Furthermore, we show that the CG potentials from OZ-HNC can be used to reduce the number of iterations and hence the computational cost of the iterative systematic coarse-graining approaches, like IBI and relative entropy minimization.
粗粒化(CG)分子动力学(MD)模拟已成为研究多尺度系统(从原子尺度到介观尺度)的流行方法。在 CGMD 中,将几个原子映射到单个 CG 珠上,并确定 CG 珠之间的有效相互作用。迭代粗粒化方法,如迭代 Boltzmann 反演(IBI),计算成本高,并且可能存在收敛问题。在本文中,我们提出了一种基于奥恩斯坦-泽尔尼克(OZ)和超网链(HNC)积分方程理论的直接且计算效率高的粗粒化理论方法。我们通过粗粒化一个体相水系统、一个水-甲醇混合物系统和一个电解质系统来演示 OZ-HNC 基 CG 方法。我们表明,从 OZ-HNC 基粗粒化获得的 CG 势的准确性可与迭代系统粗粒化方法(如 IBI 和相对熵最小化)相媲美。此外,我们表明,OZ-HNC 的 CG 势可用于减少迭代次数,从而降低迭代系统粗粒化方法(如 IBI 和相对熵最小化)的计算成本。