纳米技术
多样性(控制论)
分子动力学
计算机科学
统计物理学
材料科学
生化工程
机械工程
工程类
化学
物理
人工智能
计算化学
出处
期刊:Inorganic materials series
日期:2021-01-01
卷期号:: 79-121
标识
DOI:10.1039/9781839163319-00079
摘要
In this chapter, the ability for computational chemistry methods to predict and study the mechanical properties of materials is outlined. These properties are key to understanding the physical response of a material to an external force. This is especially important when considering the stability of a given system to experimental conditions. There are a variety of approaches to consider that either use geometry optimisation, molecular dynamics or even machine learning to quantify important mechanical criteria. This complete characterisation of the mechanical properties for a wide range of different chemical systems has enabled the discovery, and in some cases engineering, of several outstanding phenomena that on first glance appear impossible. Atomistic simulations are vital in materials science to provide microscopic understanding and lead research toward new and amazing materials.
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