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用于实现聚合物动力学温度可转移粗粒化的能量重整化

Energy-Renormalization for Achieving Temperature Transferable Coarse-Graining of Polymer Dynamics.

作者信息

Xia Wenjie, Song Jake, Jeong Cheol, Hsu David D, Phelan Frederick R, Douglas Jack F, Keten Sinan

机构信息

Materials Science & Engineering Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States.

Department of Civil & Environmental Engineering, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208-3109, United States.

出版信息

Macromolecules. 2017;50. doi: 10.1021/acs.macromol.7b01717.

Abstract

The bottom-up prediction of the properties of polymeric materials based on molecular dynamics simulation is a major challenge in soft matter physics. Coarse-grained (CG) models are often employed to access greater spatiotemporal scales required for many applications, but these models normally experience significantly altered thermodynamics and highly accelerated dynamics due to the reduced number of degrees of freedom upon coarse-graining. While CG models can be calibrated to meet certain properties at particular state points, there is unfortunately no coarse-graining method that allows for modeling of polymer dynamics over a wide temperature range. Here, we pragmatically address this problem by "correcting" for deviations in activation free energies that occur upon coarse-graining the dynamics of a model polymeric material (polystyrene). In particular, we propose a new strategy based on concepts drawn from the Adam-Gibbs (AG) theory of glass formation. Namely we renormalize the cohesive interaction strength and effective interaction length-scale parameters to modify the activation free energy. We show that this energy-renormalization method for CG modeling allows accurate prediction of atomistic dynamics over the Arrhenius regime, the non-Arrhenius regime of glass formation, and even the non-equilibrium glassy regime, thus allowing for the predictive modeling of dynamic properties of polymer over the entire range of glass formation. Our work provides a practical scheme for establishing temperature transferable coarse-grained models for predicting and designing the properties of polymeric materials.

摘要

基于分子动力学模拟自下而上预测聚合材料的性质是软物质物理学中的一项重大挑战。粗粒化(CG)模型常被用于处理许多应用所需的更大时空尺度,但由于粗粒化后自由度数量减少,这些模型通常会经历显著改变的热力学和高度加速的动力学。虽然CG模型可以校准以在特定状态点满足某些性质,但遗憾的是,没有一种粗粒化方法能够在很宽的温度范围内对聚合物动力学进行建模。在此,我们通过“校正”在对模型聚合材料(聚苯乙烯)动力学进行粗粒化时出现的活化自由能偏差,切实解决了这个问题。具体而言,我们基于从玻璃形成的亚当 - 吉布斯(AG)理论中汲取的概念提出了一种新策略。也就是说,我们对内聚相互作用强度和有效相互作用长度尺度参数进行重新归一化,以修改活化自由能。我们表明,这种用于CG建模的能量重新归一化方法能够在阿累尼乌斯区域、玻璃形成的非阿累尼乌斯区域甚至非平衡玻璃态区域准确预测原子动力学,从而能够在整个玻璃形成范围内对聚合物的动态性质进行预测建模。我们的工作为建立用于预测和设计聚合材料性质的温度可转移粗粒化模型提供了一个实用方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6192/6463524/982d9e075d4a/nihms-1506539-f0002.jpg

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