Ultrahigh-efficient material informatics inverse design of thermal metamaterials for visible-infrared-compatible camouflage

Wang Xi, Yun-Jo Lee, Shilv Yu, Zihe Chen, Junichiro Shiomi, Sun-Kyung Kim () and Run Hu ()
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Wang Xi: Huazhong University of Science and Technology
Yun-Jo Lee: Kyung Hee University
Shilv Yu: Huazhong University of Science and Technology
Zihe Chen: Huazhong University of Science and Technology
Junichiro Shiomi: University of Tokyo
Sun-Kyung Kim: Kyung Hee University
Run Hu: Huazhong University of Science and Technology

Nature Communications, 2023, vol. 14, issue 1, 1-10

Abstract: Abstract Multispectral camouflage technologies, especially in the most frequently-used visible and infrared (VIS-IR) bands, are in increasing demand for the ever-growing multispectral detection technologies. Nevertheless, the efficient design of proper materials and structures for VIS-IR camouflage is still challenging because of the stringent requirement for selective spectra in a large VIS-IR wavelength range and the increasing demand for flexible color and infrared signal adaptivity. Here, a material-informatics-based inverse design framework is proposed to efficiently design multilayer germanium (Ge) and zinc sulfide (ZnS) metamaterials by evaluating only ~1% of the total candidates. The designed metamaterials exhibit excellent color matching and infrared camouflage performance from different observation angles and temperatures through both simulations and infrared experiments. The present material informatics inverse design framework is highly efficient and can be applied to other multi-objective optimization problems beyond multispectral camouflage.

Date: 2023
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DOI: 10.1038/s41467-023-40350-6

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