Nature Reviews Materials, volume 4, issue 5, pages 331-348

Structure prediction drives materials discovery

Oganov A. R. ^{1, 2, 3}

Pickard C. J. ^{4, 5}

Zhu Qiang ⁶

Needs Richard J. ⁷

Hide authors affiliations Show authors affiliations: 7 affiliations

Skolkovo Institute of Science and technology, Moscow, Russia |

Moscow Institute of Physics and Technology, Dolgoprudny, Russia |

International Centre for Materials Discovery, Northwestern Polytechnical University, Xi’an, China |

⁴

Department of Materials Sciences & Metallurgy, University of Cambridge, Cambridge, UK |

⁵

Advanced Institute for Materials Research, Tohoku University, Aoba, Sendai, Japan |

⁶

Department of Physics and Astronomy, High Pressure Science and Engineering Center, University of Nevada Las Vegas, Las Vegas, USA |

⁷

TCM Group, Cavendish Laboratory, University of Cambridge, Cambridge, UK |

Publication type: Journal Article

Publication date: 2019-04-04

Springer Nature

Journal: Nature Reviews Materials

Quartile SCImago

Quartile WOS

Impact factor: 83.5

ISSN: 20588437

DOI: 10.1038/s41578-019-0101-8

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Materials Chemistry

Surfaces, Coatings and Films

Electronic, Optical and Magnetic Materials

Biomaterials

Energy (miscellaneous)

Abstract

Progress in the discovery of new materials has been accelerated by the development of reliable quantum-mechanical approaches to crystal structure prediction. The properties of a material depend very sensitively on its structure; 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 optimization and relying on little or no empirical knowledge, have been used to study crystalline structures, point defects, surfaces and interfaces. In this Review, we discuss structure prediction methods, examining their potential for the study of different materials systems, and present examples of computationally driven discoveries of new materials — including superhard materials, superconductors and organic materials — that will enable new technologies. Advances in first-principle structure predictions also lead to a better understanding of physical and chemical phenomena in materials. Recent breakthroughs in crystal structure prediction have enabled the discovery of new materials and of new physical and chemical phenomena. This Review surveys structure prediction methods and presents examples of results in different classes of materials.

By date By citations

Citations by journals

	5 10 15 20 25
Physical Review B	Physical Review B, 23, 5.82% Physical Review B 23 publications, 5.82%
Journal of Chemical Physics	Journal of Chemical Physics, 17, 4.3% Journal of Chemical Physics 17 publications, 4.3%
npj Computational Materials	npj Computational Materials, 13, 3.29% npj Computational Materials 13 publications, 3.29%
Journal of Physical Chemistry Letters	Journal of Physical Chemistry Letters, 12, 3.04% Journal of Physical Chemistry Letters 12 publications, 3.04%
Journal of Physical Chemistry C	Journal of Physical Chemistry C, 12, 3.04% Journal of Physical Chemistry C 12 publications, 3.04%
Physical Review Materials	Physical Review Materials, 11, 2.78% Physical Review Materials 11 publications, 2.78%
Journal of Physics Condensed Matter	Journal of Physics Condensed Matter, 8, 2.03% Journal of Physics Condensed Matter 8 publications, 2.03%
Physical Chemistry Chemical Physics	Physical Chemistry Chemical Physics, 8, 2.03% Physical Chemistry Chemical Physics 8 publications, 2.03%
Chemical Science	Chemical Science, 8, 2.03% Chemical Science 8 publications, 2.03%
Chemical Reviews	Chemical Reviews, 7, 1.77% Chemical Reviews 7 publications, 1.77%
Applied Physics Reviews	Applied Physics Reviews, 6, 1.52% Applied Physics Reviews 6 publications, 1.52%
Physical Review Letters	Physical Review Letters, 6, 1.52% Physical Review Letters 6 publications, 1.52%
Journal of the American Chemical Society	Journal of the American Chemical Society, 6, 1.52% Journal of the American Chemical Society 6 publications, 1.52%
Computational Materials Science	Computational Materials Science, 6, 1.52% Computational Materials Science 6 publications, 1.52%
CrystEngComm	CrystEngComm, 6, 1.52% CrystEngComm 6 publications, 1.52%
Chemistry of Materials	Chemistry of Materials, 5, 1.27% Chemistry of Materials 5 publications, 1.27%
Nature Communications	Nature Communications, 5, 1.27% Nature Communications 5 publications, 1.27%
Angewandte Chemie - International Edition	Angewandte Chemie - International Edition, 5, 1.27% Angewandte Chemie - International Edition 5 publications, 1.27%
Crystal Growth and Design	Crystal Growth and Design, 5, 1.27% Crystal Growth and Design 5 publications, 1.27%
Computer Physics Communications	Computer Physics Communications, 5, 1.27% Computer Physics Communications 5 publications, 1.27%
Physical Review Research	Physical Review Research, 5, 1.27% Physical Review Research 5 publications, 1.27%
Crystals	Crystals, 5, 1.27% Crystals 5 publications, 1.27%
Angewandte Chemie	Angewandte Chemie, 5, 1.27% Angewandte Chemie 5 publications, 1.27%
Journal of Physical Chemistry A	Journal of Physical Chemistry A, 5, 1.27% Journal of Physical Chemistry A 5 publications, 1.27%
Journal of Applied Physics	Journal of Applied Physics, 4, 1.01% Journal of Applied Physics 4 publications, 1.01%
Acta Materialia	Acta Materialia, 4, 1.01% Acta Materialia 4 publications, 1.01%
Advanced Materials	Advanced Materials, 4, 1.01% Advanced Materials 4 publications, 1.01%
Advanced Science	Advanced Science, 4, 1.01% Advanced Science 4 publications, 1.01%
Inorganic Chemistry	Inorganic Chemistry, 4, 1.01% Inorganic Chemistry 4 publications, 1.01%
	5 10 15 20 25

Citations by publishers

	10 20 30 40 50 60 70 80
American Chemical Society (ACS)	American Chemical Society (ACS), 80, 20.25% American Chemical Society (ACS) 80 publications, 20.25%
Elsevier	Elsevier, 55, 13.92% Elsevier 55 publications, 13.92%
American Physical Society (APS)	American Physical Society (APS), 47, 11.9% American Physical Society (APS) 47 publications, 11.9%
Royal Society of Chemistry (RSC)	Royal Society of Chemistry (RSC), 41, 10.38% Royal Society of Chemistry (RSC) 41 publications, 10.38%
Springer Nature	Springer Nature, 41, 10.38% Springer Nature 41 publications, 10.38%
Wiley	Wiley, 35, 8.86% Wiley 35 publications, 8.86%
American Institute of Physics (AIP)	American Institute of Physics (AIP), 34, 8.61% American Institute of Physics (AIP) 34 publications, 8.61%
IOP Publishing	IOP Publishing, 17, 4.3% IOP Publishing 17 publications, 4.3%
Multidisciplinary Digital Publishing Institute (MDPI)	Multidisciplinary Digital Publishing Institute (MDPI), 9, 2.28% Multidisciplinary Digital Publishing Institute (MDPI) 9 publications, 2.28%
Frontiers Media S.A.	Frontiers Media S.A., 4, 1.01% Frontiers Media S.A. 4 publications, 1.01%
Taylor & Francis	Taylor & Francis, 4, 1.01% Taylor & Francis 4 publications, 1.01%
American Association for the Advancement of Science (AAAS)	American Association for the Advancement of Science (AAAS), 3, 0.76% American Association for the Advancement of Science (AAAS) 3 publications, 0.76%
Oxford University Press	Oxford University Press, 3, 0.76% Oxford University Press 3 publications, 0.76%
International Union of Crystallography (IUCr)	International Union of Crystallography (IUCr), 2, 0.51% International Union of Crystallography (IUCr) 2 publications, 0.51%
Chinese Physical Society	Chinese Physical Society, 2, 0.51% Chinese Physical Society 2 publications, 0.51%
Annual Reviews	Annual Reviews, 2, 0.51% Annual Reviews 2 publications, 0.51%
The Royal Society	The Royal Society, 1, 0.25% The Royal Society 1 publication, 0.25%
Tech Science Press	Tech Science Press, 1, 0.25% Tech Science Press 1 publication, 0.25%
Cambridge University Press	Cambridge University Press, 1, 0.25% Cambridge University Press 1 publication, 0.25%
Institute for Operations Research and the Management Sciences (INFORMS)	Institute for Operations Research and the Management Sciences (INFORMS), 1, 0.25% Institute for Operations Research and the Management Sciences (INFORMS) 1 publication, 0.25%
Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii	Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii, 1, 0.25% Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii 1 publication, 0.25%
Hans Publishers	Hans Publishers, 1, 0.25% Hans Publishers 1 publication, 0.25%
Proceedings of the National Academy of Sciences (PNAS)	Proceedings of the National Academy of Sciences (PNAS), 1, 0.25% Proceedings of the National Academy of Sciences (PNAS) 1 publication, 0.25%
Ceramic Society of Japan	Ceramic Society of Japan, 1, 0.25% Ceramic Society of Japan 1 publication, 0.25%
Walter de Gruyter	Walter de Gruyter, 1, 0.25% Walter de Gruyter 1 publication, 0.25%
	10 20 30 40 50 60 70 80

We do not take into account publications that without a DOI.
Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
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Oganov A. R. et al. Structure prediction drives materials discovery // Nature Reviews Materials. 2019. Vol. 4. No. 5. pp. 331-348.

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Oganov A. R., Pickard C. J., Zhu Q., Needs R. J. Structure prediction drives materials discovery // Nature Reviews Materials. 2019. Vol. 4. No. 5. pp. 331-348.

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RIS Copy

TY - JOUR

DO - 10.1038/s41578-019-0101-8

UR - https://doi.org/10.1038%2Fs41578-019-0101-8

TI - Structure prediction drives materials discovery

T2 - Nature Reviews Materials

AU - Oganov, A. R.

AU - Pickard, C. J.

AU - Needs, Richard J.

AU - Zhu, Qiang

PY - 2019

DA - 2019/04/04 00:00:00

PB - Springer Nature

SP - 331-348

IS - 5

VL - 4

SN - 2058-8437

ER -

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@article{2019_Oganov,

author = {A. R. Oganov and C. J. Pickard and Richard J. Needs and Qiang Zhu},

title = {Structure prediction drives materials discovery},

journal = {Nature Reviews Materials},

year = {2019},

volume = {4},

publisher = {Springer Nature},

month = {apr},

url = {https://doi.org/10.1038%2Fs41578-019-0101-8},

number = {5},

pages = {331--348},

doi = {10.1038/s41578-019-0101-8}

}

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Oganov, A. R., et al. “Structure prediction drives materials discovery.” Nature Reviews Materials, vol. 4, no. 5, Apr. 2019, pp. 331-348. https://doi.org/10.1038%2Fs41578-019-0101-8.

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Nature Reviews Materials

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83.5

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20588437 (Electronic)

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Materials Design Laboratory

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