基于回归驱动粗粒化的缺陷二维聚合物弹性性能研究。

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation Pub Date : 2025-10-23 DOI:10.1021/acs.jctc.5c01339

David Bodesheim, Alexander Croy, Gianaurelio Cuniberti

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引用次数: 0

摘要

二维聚合物（2DPs）是一类有趣的聚合物，由于它们的网状合成组装，这使它们成为设计具有特定目标性能的材料的理想平台。预测和理解其弹性行为对其应用至关重要。然而，由于合成的2dp中普遍存在缺陷，对其性质的实际计算仍然具有计算挑战性。在这里，我们引入了一种基于弹性梁的粗粒化（CG）方法，称为MikadoRR，其参数从简单的基于回归的拟合中提取。这种方法使我们能够精确地计算到微观尺度上有缺陷的2dp的弹性特性。此外，我们证明了定制弹性性能的2dp设计原则可以从这个CG模型中推导出来。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Elastic Properties of Defective 2D Polymers from Regression Driven Coarse-Graining.

Two-dimensional polymers (2DPs) are an interesting class of polymers due to their reticular synthetic assembly, which make them an ideal platform for designing materials with specific target properties. Predicting and understanding their elastic behavior is crucial for their application. However, a realistic calculation of their properties remains computationally challenging due to the ubiquitous presence of defects in synthesized 2DPs. Here, we introduce a coarse-graining (CG) approach based on elastic beams called MikadoRR with parameters extracted from a simple regression-based fitting. This approach allows us to accurately calculate the elastic properties of defective 2DPs up to the microscale. Furthermore, we show that design principles of 2DPs for tailored elastic properties can be derived from this CG model.

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来源期刊

Journal of Chemical Theory and Computation 化学-物理：原子、分子和化学物理

CiteScore

9.90

自引率

16.40%

发文量

568

审稿时长

1 months

期刊介绍： The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.