计算机科学
表征(材料科学)
鉴定(生物学)
材料科学
适应(眼睛)
纳米技术
电子结构
系统工程
工程类
生物
光学
物理
植物
量子力学
作者
Nicola Marzari,Andrea Ferretti,Chris Wolverton
出处
期刊:Nature Materials
[Nature Portfolio]
日期:2021-05-27
卷期号:20 (6): 736-749
被引量:182
标识
DOI:10.1038/s41563-021-01013-3
摘要
The accuracy and efficiency of electronic-structure methods to understand, predict and design the properties of materials has driven a new paradigm in research. Simulations can greatly accelerate the identification, characterization and optimization of materials, with this acceleration driven by continuous progress in theory, algorithms and hardware, and by adaptation of concepts and tools from computer science. Nevertheless, the capability to identify and characterize materials relies on the predictive accuracy of the underlying physical descriptions, and on the ability to capture the complexity of realistic systems. We provide here an overview of electronic-structure methods, of their application to the prediction of materials properties, and of the different strategies employed towards the broader goals of materials design and discovery. Simulations can be used to accelerate the characterization and discovery of materials. Here we Review how electronic-structure methods such as density functional theory work, what properties they can be used to predict and how they can be used to design materials.
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