MoSDeF, a Python Framework Enabling Large-Scale Computational Screening of Soft Matter: Application to Chemistry-Property Relationships in Lubricating Monolayer Films
MoSDeF, a Python Framework Enabling Large-Scale Computational Screening of Soft Matter: Application to Chemistry-Property Relationships in Lubricating Monolayer Films
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MoSDeF，一种能够对软物质进行大规模计算筛选的 Python 框架：在润滑单层薄膜中的化学性质关系的应用
DOI：
10.1021/acs.jctc.9b01183
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发表时间：
2020
影响因子：
5.5
通讯作者：
MCabe, Clare
中科院分区：
文献类型：
--
作者：
Summers, Andrew Z.;Gilmer, Justin B.;Iacovella, Christopher R.;Cummings, Peter T.;MCabe, Clare
我们演示了如何使用最近开发的基于Python的分子模拟和设计框架(MoSDeF)来进行功能化单层膜的分子动力学筛选，重点是摩擦学效果。MoSDeF是一个开放源码的包，它允许软物质系统的程序化构建和参数化，并支持真正的(可转移、可重复、可供他人使用和可扩展的)模拟。启用MoSDeF的筛选可识别同时显示低摩擦系数和附着力的几种薄膜化学成分。此外，我们还开发了一个使用RDKit化学信息学库和SCRKIT学习机器学习库的Python库，该库允许为功能化单层膜的摩擦学开发预测模型，并基于筛选数据使用该模型提取关于最大程度影响摩擦学的端基特征的信息。
We demonstrate how the recently developed Python-based Molecular Simulation and Design Framework (MoSDeF) can be used to perform molecular dynamics screening of functionalized monolayer films, focusing on tribological effectiveness. MoSDeF is an open-source package that allows for the programmatic construction and parametrization of soft matter systems and enables TRUE (transferable, reproducible, usable by others, and extensible) simulations. The MoSDeF-enabled screening identifies several film chemistries that simultaneously show low coefficients of friction and adhesion. We additionally develop a Python library that utilizes the RDKit cheminformatics library and the scikit-learn machine learning library that allows for the development of predictive models for the tribology of functionalized monolayer films and use this model to extract information on terminal group characteristics that most influence tribology, based on the screening data.