Material Performance Prediction
Material Performance Prediction is a computational methodology that fundamentally enables the forecasting of functional behaviors and mechanical responses of materials under specified conditions through data-driven or physics-informed models.
1.5K
Publications
79.4K
Citations
5.8K
Authors
1.6K
Institutions
Publications per year
2017–2026
1.1K
Parents
1.5K
Materials discovery and design using machine learning
Yue Liu, Tianlu Zhao, Wangwei Ju et al. · Journal of Materiomics · 2017 · 1.2K citations · Full text
Natural Sciences, Materials Engineering, Materials Science +16
Machine learning in materials science
Jing Wei, Xuan Chu, Xiangyu Sun et al. · InfoMat · 2019 · 1K citations · Full text
Natural Sciences, Materials Engineering, Materials Science +14
1–5 of 1.5K
5.8K
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Peter the Great St. Petersburg Polytechnic University, Russia
9 publications · 612 citations
9
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9
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8
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1–5 of 5.8K
1.6K

University of Science and Technology Beijing
Beijing, China
23 h-index
137 publications
6K citations
COMSATS University Islamabad
Islamabad, Pakistan
23 h-index
42 publications
3.5K citations
Northwestern University
Evanston, United States
18 h-index
85 publications
9.8K citations

Harbin Institute of Technology
Harbin, China
18 h-index
67 publications
2.8K citations

Shanghai University
Shanghai, China
17 h-index
63 publications
6.9K citations

Shanghai Jiao Tong University
Shanghai, China
17 h-index
71 publications
4.2K citations

Centre National de la Recherche Scientifique
Paris, France
17 h-index
43 publications
3.2K citations

Chinese Academy of Sciences
Beijing, China
16 h-index
61 publications
2.2K citations
1–8 of 1.6K
44 publications · 3.4K citations
30
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40 publications · 1.9K citations
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32 publications · 1.7K citations
26
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35 publications · 2.2K citations
24
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29 publications · 1.3K citations
23
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