High-throughput Materials Screening
High-Throughput Materials Screening is a computational methodology in materials science that systematically evaluates large collections of materials properties using automated simulations and data analytics to accelerate the discovery and optimization of novel materials.
1.3K
Publications
124.5K
Citations
4.7K
Authors
1K
Institutions
Publications per year
2017–2026
1K
1.3K
1–5 of 1.3K
4.7K
Lawrence Berkeley National Laboratory, United States
25 publications · 17.6K citations
23
h-index
16
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14
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14
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14
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1–5 of 4.7K
1K
Northwestern University
Evanston, United States
40 h-index
174 publications
50.3K citations

Lawrence Berkeley National Laboratory
Berkeley, United States
35 h-index
171 publications
177.1K citations
University of California, Berkeley
Berkeley, United States
34 h-index
103 publications
25.9K citations
Massachusetts Institute of Technology
Cambridge, United States
30 h-index
169 publications
159.6K citations
National Institute of Standards and Technology
Gaithersburg, United States
28 h-index
128 publications
18.8K citations

Chinese Academy of Sciences
Beijing, China
27 h-index
143 publications
6.4K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
20 h-index
71 publications
11.1K citations
University of Chinese Academy of Sciences
Beijing, China
20 h-index
89 publications
4.5K citations
1–8 of 1K
65 publications · 8.1K citations
44
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56 publications · 7K citations
38
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39 publications · 2.6K citations
27
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38 publications · 2.6K citations
27
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28 publications · 4K citations
26
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1–5