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粗粒化方法在聚合物性能估算中的表现:与原子模型的比较

Performance of Coarse Graining in Estimating Polymer Properties: Comparison with the Atomistic Model.

作者信息

Miwatani Ryota, Takahashi Kazuaki Z, Arai Noriyoshi

机构信息

Department of Mechanical Engineering, Kindai University, 3-4-1 Kowakae, Higashiosaka, Osaka 577-8522, Japan.

Research Center for Computational Design of Advanced Functional Materials, National Institute of Advanced Industrial Science and Technology (AIST), Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan.

出版信息

Polymers (Basel). 2020 Feb 8;12(2):382. doi: 10.3390/polym12020382.

Abstract

Combining atomistic and coarse-grained (CG) models is a promising approach for quantitative prediction of polymer properties. However, the gaps between the length and time scales of atomistic and CG models still need to be bridged. Here, the scale gaps of the atomistic model of polyethylene melts, the bead-spring Kremer-Grest model, and dissipative particle dynamics with the slip-spring model were investigated. A single set of spatial and temporal scaling factors was determined between the atomistic model and each CG model. The results of the CG models were rescaled using the set of scaling factors and compared with those of the atomistic model. For each polymer property, a threshold value indicating the onset of static or dynamic universality of polymers was obtained. The scaling factors also revealed the computational efficiency of each CG model with respect to the atomistic model. The performance of the CG models of polymers was systematically evaluated in terms of both the accuracy and computational efficiency.

摘要

结合原子模型和粗粒化(CG)模型是定量预测聚合物性能的一种很有前景的方法。然而,原子模型和CG模型在长度和时间尺度上的差距仍有待弥合。在此,研究了聚乙烯熔体原子模型、珠簧Kremer-Grest模型以及带有滑移弹簧模型的耗散粒子动力学之间的尺度差距。确定了原子模型与每个CG模型之间的一组单一的空间和时间缩放因子。使用该组缩放因子对CG模型的结果进行重新缩放,并与原子模型的结果进行比较。对于每种聚合物性能,获得了一个表明聚合物静态或动态普适性开始的阈值。缩放因子还揭示了每个CG模型相对于原子模型的计算效率。从准确性和计算效率两方面系统地评估了聚合物CG模型的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64dd/7077424/b9151bc6eb17/polymers-12-00382-g001.jpg

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