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Machine learning-enabled high-entropy Invar alloy discovery

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Rao,  Ziyuan
Artificial Intelligence for Material Science, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Wei,  Ye
Hydrogen in Energy Materials, Project Groups, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Tung,  Po-Yen
Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Raabe,  Dierk
Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Citation

Rao, Z., Wei, Y., Tung, P.-Y., Xie, R., Zhang, H., Bauer, S., et al. (2023). Machine learning-enabled high-entropy Invar alloy discovery. Talk presented at Accelerated Discovery of new materials, 787 WE-Heraeus-Seminar. Physikzentrum Bad Honnef, Germany. 2023-05-15 - 2023-05-18.


Cite as: https://hdl.handle.net/21.11116/0000-000F-DC83-5
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