Abstract
The chemical space for designing materials is practically infinite. This makes disruptive progress by traditional physics-based modeling alone challenging. Yet, training data for identifying composition–structure–property relations by artificial intelligence are sparse. We discuss opportunities to discover new chemically complex materials by hybrid methods where physics laws are combined with artificial intelligence.
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The authors are grateful for financial support by the BIGmax research network of the Max-Planck Society (https://www.bigmax.mpg.de/).
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Raabe, D., Mianroodi, J.R. & Neugebauer, J. Accelerating the design of compositionally complex materials via physics-informed artificial intelligence. Nat Comput Sci 3, 198–209 (2023). https://doi.org/10.1038/s43588-023-00412-7
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DOI: https://doi.org/10.1038/s43588-023-00412-7
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