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Identifying Chemically Similar Multiphase Nanoprecipitates in Compositionally Complex Non-Equilibrium Oxides via Machine Learning

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ML_FUEL_CM_COMMSMAT

Title

Identifying chemically similar multiphase nanoprecipitates in compositionally complex non-equilibrium oxides via machine learning

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Journal Communications Materials

DOI 10.1038/s43246-022-00244-4

Publication Date 2022-04-19

This article is available online here https://doi.org/10.1038/s43246-022-00244-4 or as a PDF here https://www.nature.com/articles/s43246-022-00244-4.pdf.

This article is published under the Creative Commons Attribution license which allows users to read, copy, distribute and make derivative works, as long as the author of the original work is cited. You may self archive this article in any location of your choice, including on your own website, an institutional repository or funder’s repository and make it publicly available immediately.

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Citation Information

This article can be cited by its DOI 10.1038/s43246-022-00244-4 in the following form: Author, Journal Title, Year, DOI

If you have any questions, you could reach out to the corresponding authors in this paper. Correspondence and requests for materials should be addressed to Keyou S. Mao, (kmao@eng.famu.fsu.edu); Tyler J. Gerczak, (gerczaktj@ornl.gov); Chad M. Parish, (parishcm@ornl.gov;) or Philip D. Edmondson (edmondsonpd@ornl.gov).

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Identifying Chemically Similar Multiphase Nanoprecipitates in Compositionally Complex Non-Equilibrium Oxides via Machine Learning

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