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Structure Prediction Drives Materials Discovery

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Oganov, Artem 
Pickard, Christopher  ORCID logo  https://orcid.org/0000-0002-9684-5432
Zhu, Qiang 

Abstract

Progress in the discovery of new materials has recently been driven by the development of reliable quantum-mechanical approaches to crystal structure prediction. The properties of a material depend very sensitively on its structure, and therefore structure prediction is the key to computational materials discovery. Structure prediction was considered to be a formidable problem, but the development of new computational tools has allowed the structures of many new and increasingly complex materials to be anticipated. These widely applicable methods, based on global optimisation and relying on little or no empirical knowledge, have been used to study crystalline structures, point defects, surfaces and interfaces. In this review we present examples of computationally-driven discovery of new materials that will enable new technologies and lead to a better understanding of physical and chemical phenomena in materials.

Description

Keywords

40 Engineering, 4016 Materials Engineering, Generic health relevance

Journal Title

Nature Reviews Materials

Conference Name

Journal ISSN

2058-8437
2058-8437

Volume Title

Publisher

Springer Nature
Sponsorship
Engineering and Physical Sciences Research Council (EP/P022596/1)
Engineering and Physical Sciences Research Council (EP/P034616/1)