Materials Structure Prediction
Materials Structure Prediction is a computational methodology within materials science that identifies the most stable atomic arrangements of a given material by predicting its crystal structure from chemical composition and physical principles.
695
Publications
46.6K
Citations
2.3K
Authors
778
Institutions
Publications per year
2017–2026
442
Parents
695
<i>Ab initio</i>random structure searching
Chris J. Pickard, R. J. Needs · Journal of Physics Condensed Matter · 2011 · 1.2K citations · Full text
Scaling deep learning for materials discovery
Amil Merchant, Simon Batzner, Samuel S. Schoenholz et al. · Nature · 2023 · 1.2K citations · Full text
1–5 of 695
2.3K
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Max Planck Institute for Solid State Research, Germany
8 publications · 276 citations
8
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1–5 of 2.3K
778

Centre National de la Recherche Scientifique
Paris, France
22 h-index
62 publications
5.2K citations
Jilin University
Changchun, China
19 h-index
87 publications
12.2K citations
University of Cambridge
Cambridge, United Kingdom
17 h-index
51 publications
7K citations
Northwestern University
Evanston, United States
14 h-index
44 publications
3.2K citations

Lawrence Berkeley National Laboratory
Berkeley, United States
13 h-index
28 publications
1.4K citations
National Institute for Materials Science
Tsukuba, Japan
13 h-index
30 publications
1.9K citations
Los Alamos National Laboratory
Los Alamos, United States
13 h-index
28 publications
4.6K citations

Chinese Academy of Sciences
Beijing, China
12 h-index
19 publications
963 citations
1–8 of 778
25 publications · 1.1K citations
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24 publications · 1.2K citations
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19 publications · 2.7K citations
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18 publications · 1.2K citations
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18 publications · 2.3K citations
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