Ha, Chan Soo http://orcid.org/0000-0003-3314-2657
Yao, Desheng http://orcid.org/0000-0003-2069-1112
Xu, Zhenpeng
Liu, Chenang
Liu, Han http://orcid.org/0000-0002-4899-9998
Elkins, Daniel
Kile, Matthew
Deshpande, Vikram http://orcid.org/0000-0003-3899-3573
Kong, Zhenyu http://orcid.org/0000-0002-8827-502X
Bauchy, Mathieu
Zheng, Xiaoyu http://orcid.org/0000-0001-8685-5728
Funding for this research was provided by:
United States Department of Defense | United States Navy | ONR | Office of Naval Research Global (N00014-20-1-2504:P00001)
National Science Foundation (2119643)
United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (FA9550‐18‐1‐0299)
Article History
Received: 29 November 2022
Accepted: 11 August 2023
First Online: 18 September 2023
Competing interests
: The Regents of the University of California, a California Corporation has filed a U.S. provisional application (serial no. 63/456200) for the presented machine learning-based rapid inverse design methodology (pending). Inventors include X.Z., C.H., D.Y., and M.B. The remaining authors, Z.X., C.L., H.L., D.E., M.K., V.D., and Z.K. declare no financial and non-financial competing interests in the subject matter or materials discussed in this article.