Abstract
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.
Original language | English (US) |
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Pages (from-to) | 736-749 |
Number of pages | 14 |
Journal | Nature materials |
Volume | 20 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2021 |
Funding
We acknowledge all the students, researchers and colleagues that developed the theories, algorithms and codes underpinning the research sketched here and that could not always be explicitly cited, but are indirectly present through the references. We are grateful for support from the Swiss NSF for the National Centre for Competence in Research MARVEL on \u2018Computational Design and Discovery of Novel Materials\u2019 (N.M.), from the EU Commission for the MaX Centre of Excellence on \u2018Materials Design at the eXascale\u2019 under grant no. 824143 (A.F., N.M.), and from the US Department of Commerce and the National Institute of Standards and Technology as part of the Center for Hierarchical Materials Design (CHiMaD) under grant no. 70NANB14H012 (C.W.).
ASJC Scopus subject areas
- General Chemistry
- General Materials Science
- Condensed Matter Physics
- Mechanics of Materials
- Mechanical Engineering