Fraux Guillaume, Chibani Siwar, Coudert François-Xavier
Chimie ParisTech , PSL University , CNRS, Institut de Recherche de Chimie, 75005 Paris , France.
Philos Trans A Math Phys Eng Sci. 2019 Jul 15;377(2149):20180220. doi: 10.1098/rsta.2018.0220.
The last decade has seen an explosion of the family of framework materials and their study, from both the experimental and computational points of view. We propose here a short highlight of the current state of methodologies for modelling framework materials at multiple scales, putting together a brief review of new methods and recent endeavours in this area, as well as outlining some of the open challenges in this field. We will detail advances in atomistic simulation methods, the development of material databases and the growing use of machine learning for the prediction of properties. This article is part of the theme issue 'Mineralomimesis: natural and synthetic frameworks in science and technology'.
在过去十年中，从实验和计算的角度来看，框架材料家族及其研究出现了爆发式增长。我们在此简要介绍一下当前多尺度模拟框架材料的方法现状，汇总该领域新方法和近期研究的简要综述，并概述一些尚未解决的挑战。我们将详细介绍原子模拟方法的进展、材料数据库的发展以及机器学习在性能预测方面越来越多的应用。本文是主题为“矿物模拟：科学与技术中的天然和合成框架”的一部分。
