多光谱图像
伪装
材料科学
吸收(声学)
微波食品加热
光学
计算机科学
光电子学
遥感
发射率
基质(水族馆)
透射率
光子学
纳米尺度
红外线的
作者
Can Li,Leilei Liang,Bing Zhang,Yi Yang,Guangbin Ji
标识
DOI:10.1007/s40820-026-02247-z
摘要
Abstract Achieving omnidirectional multispectral compatible camouflage remains a significant challenge due to the pronounced disparities in electromagnetic wavelengths and constraints on the response mechanisms of natural materials. Herein, neural networks are employed to intelligently optimize the design of multiscale impedance-gradient (IG) metadevices tailored for multispectral compatibility. The macro-gradient unit is engineered with precise impedance matching and high rotational symmetry to provide exceptional microwave ultra-broadband absorption (2–18 GHz), with insensitivity angles reaching 60°. By integrating a polyimide foam substrate with an MXene-functionalized nanostructured photochromic top layer, the finalized device exhibits remarkable infrared thermal insulation (ΔT $$\approx$$ ≈ 65 °C) and low emissivity (0.38), alongside rapid visible color change (1 ~ 2 s) enabled by nanoscale photochromic switching. Furthermore, IG metadevices deliver programmability and multimodality, alongside impact resistance (~ 30,000 N) and environmental stability. This work provides novel paradigms for the intelligent design of multispectral compatible camouflage systems adaptable to complex scenarios.
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