工作流程
力场(虚构)
计算机科学
指南针
领域(数学)
集合(抽象数据类型)
密度泛函理论
离子键合
过程(计算)
工作(物理)
能量最小化
数据挖掘
计算科学
计算化学
化学
数据库
人工智能
物理
数学
热力学
离子
操作系统
有机化学
程序设计语言
纯数学
量子力学
作者
Reinier Akkermans,Neil A. Spenley,Struan H. Robertson
标识
DOI:10.1080/08927022.2020.1808215
摘要
The ability to automatically extend and improve molecular force fields to accurately describe an ever wider range of compounds is a key enabler for the application of molecular modelling of chemicals and materials in industry. In this work we have developed a set of tools to process structural data available in well-known databases, to find deficiencies in the force field, and where necessary, automatically fit force- field parameters to on-the-fly calculated quantum data based on Density Functional Theory, supplemented by experimental data. The protocols have been applied to structures from the Maybridge, PoLyInfo and ILThermo databases, covering drug-like molecules, polymers and ionic liquids respectively. We demonstrate that the new version of the force field can type all structures in the extended data set without missing parameters, with a similar high-quality prediction of geometry (bonds, angles, torsions), energy and forces of earlier versions.
科研通智能强力驱动
Strongly Powered by AbleSci AI