Pothos: A Python Package for Polymer Chain Orientation and Microstructure Evolution Monitoring.

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2025-01-14 Epub Date: 2024-12-23 DOI:10.1021/acs.jctc.4c01216

Thomas J Barrett, Marilyn L Minus

引用次数: 0

Abstract

In the pursuit of informing experimental techniques with in silico optimizations, we propose a pip deployable Python package, pothos, to easily determine polymer crystallites within molecular dynamic melts and the chain orientation parameters of atomistic and coarse-grained simulations. The package supports the commonly used ⟨P₂⟩, ⟨P₄⟩, and ⟨P₆⟩ order parameters based on the chain chord vector and utilizes a modified DBSCAN algorithm to determine crystalline regions. The results of analysis are written to text and LAMMPS dump files for visualization and analysis.

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用于聚合物链取向和微观结构演变监测的Python包。

为了使实验技术与硅优化相结合，我们提出了一个pip可部署的Python包，pothos，以方便地确定分子动态熔体中的聚合物晶体以及原子和粗粒度模拟的链取向参数。该包支持基于链弦向量的⟨P2⟩，⟨P4⟩和⟨P6⟩的常用顺序参数，并利用改进的DBSCAN算法来确定结晶区域。分析结果被写入文本和LAMMPS转储文件，以便可视化和分析。

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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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Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere.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.