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Authors
Liang, Qiaohao https://orcid.org/0000-0002-6551-9810
Gongora, Aldair E.
Ren, Zekun
Tiihonen, Armi https://orcid.org/0000-0001-9753-6802
Liu, Zhe
Sun, Shijing https://orcid.org/0000-0002-6179-1390
Deneault, James R.
Bash, Daniil
Mekki-Berrada, Flore
Khan, Saif A. https://orcid.org/0000-0002-8990-8802
Hippalgaonkar, Kedar https://orcid.org/0000-0002-1270-9047
Maruyama, Benji
Brown, Keith A. https://orcid.org/0000-0002-2379-2018
Fisher III, John
Buonassisi, Tonio https://orcid.org/0000-0001-8345-4937
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Funding
Funding for this research was provided by:
TOTAL S.A. research grant funded through MITei
National Science Foundation (CMMI-1661412)
National Science Foundation (CMMI-1661412)
National Science Foundation (CBET-1605547)
Google
Boston University
Singapore-MIT Alliance for Research and Technology Centre
Total
United States Department of Defense | Defense Advanced Research Projects Agency (HR001118C0036)
United States Department of Defense | Defense Advanced Research Projects Agency (HR001118C0036)
United States Department of Defense | Defense Advanced Research Projects Agency (HR001118C0036)
Skolkovo Institute of Science and Technology
United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (19RHCOR089)
United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (19RHCOR089)
Agency for Science, Technology and Research (A1898b0043)
Agency for Science, Technology and Research (A1898b0043)
Agency for Science, Technology and Research (A1898b0043)
Agency for Science, Technology and Research (A1898b0043)
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Article History
Received: 16 May 2021
Accepted: 12 October 2021
First Online: 18 November 2021
Competing interests
: The authors Z.R., Z.L., D.B., K.H., T.B. declare general IP in the area of applied machine learning, and are associated with start-up efforts (xinterra<sup>™</sup>) to accelerate materials development using applied machine learning. The other authors declare no competing interests.
