Zhang Xu-Ze, Shi Rui, Lu Zhong-Yuan, Qian Hu-Jun
State Key Laboratory of Supramolecular Structure and Materials, Institute of Theoretical Chemistry, College of Chemistry, Jilin University, Changchun 130021, China.
JACS Au. 2024 Mar 13;4(3):1018-1030. doi: 10.1021/jacsau.3c00756. eCollection 2024 Mar 25.
The coarse-grained (CG) model serves as a powerful tool for the simulation of polymer systems; its reliability depends on the accurate representation of both structural and dynamical properties. However, strong correlations between structural and dynamical properties on different scales and also a strong memory effect, enforced by chain connectivity between monomers in polymer systems, render developing a chemically specific systematic CG model a formidable task. In this study, we report a systematic CG approach that combines the iterative Boltzmann inversion (IBI) method and the generalized Langevin equation (GLE) dynamics. Structural properties are ensured by using conservative CG potentials derived from the IBI method. To retrieve the correct dynamical properties in the system, we demonstrate that using a combination of a Rouse-type delta function and a time-dependent short-time kernel in the GLE simulation is practically efficient. The former can be used to adjust the long-time diffusion dynamics, and the latter can be reconstructed from an iterative procedure according to the velocity autocorrelation function (ACF) from all-atomistic (AA) simulations. Taking the polystyrene as an example, we show that not only structural properties of radial distribution function, intramolecular bond, and angle distributions can be reproduced but also dynamical properties of mean-square displacement, velocity ACF, and force ACF resulted from our CG model have quantitative agreement with the reference AA model. In addition, reasonable agreements are observed in other collective properties between our GLE-CG model and the AA simulations as well.
粗粒化(CG)模型是模拟聚合物体系的有力工具;其可靠性取决于结构和动力学性质的准确表征。然而,聚合物体系中不同尺度上结构与动力学性质之间的强相关性以及由单体间链连接性所导致的强记忆效应,使得开发具有化学特异性的系统CG模型成为一项艰巨任务。在本研究中,我们报告了一种将迭代玻尔兹曼反演(IBI)方法与广义朗之万方程(GLE)动力学相结合的系统CG方法。通过使用源自IBI方法的保守CG势来确保结构性质。为了在系统中获取正确的动力学性质,我们证明在GLE模拟中使用劳斯型δ函数和时间相关的短时核函数的组合在实际应用中是有效的。前者可用于调整长时间扩散动力学,后者可根据全原子(AA)模拟的速度自相关函数(ACF)通过迭代过程进行重构。以聚苯乙烯为例,我们表明我们的CG模型不仅能够重现径向分布函数、分子内键和角度分布等结构性质,而且均方位移、速度ACF和力ACF等动力学性质与参考AA模型具有定量一致性。此外,我们的GLE - CG模型与AA模拟在其他集体性质方面也观察到了合理的一致性。