Ultra-Broadband Microwave Absorption and Programmable Multispectral Camouflage Enabled by Neural-Network-Driven Impedance-Gradient Metadevices
Corresponding Author: Guangbin Ji
Nano-Micro Letters,
Vol. 18 (2026), Article Number: 403
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 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.
Highlights:
1 An impedance-gradient metadevice for multispectral compatible camouflage was intelligently designed using the neural network.
2 The metadevice demonstrates excellent microwave ultra-broadband absorption (2–18 GHz), infrared thermal insulation (ΔT≈65 °C), low emissivity (0.38), and rapid visible color change (1–2 s).
3 The assembled device offers programmability and multimodality while also exhibiting impact resistance (~30,000 N) and environmental stability.
Keywords
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References
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L. Liang, X. Yang, C. Li, R. Yu, B. Zhang et al., MXene-enabled pneumatic multiscale shape morphing for adaptive, programmable and multimodal radar-infrared compatible camouflage. Adv. Mater. 36(24), 2313939 (2024). https://doi.org/10.1002/adma.202313939
H. Zhang, J. Cheng, K. Liu, S.-X. Jiang, J. Zhang et al., Electric-magnetic dual-gradient structure design of thin MXene/Fe3O4 films for absorption-dominated electromagnetic interference shielding. J. Colloid Interface Sci. 678, 950–958 (2025). https://doi.org/10.1016/j.jcis.2024.08.216
Y. Li, Y. Jin, H. Raza, Y. Wang, Q. Chen et al., Dual driving strategy from micro-polarization to macroscopic conductance: tailoring optimized low-frequency and wide-band microwave absorption in high-entropy oxides. J. Mater. Sci. Technol. 235, 110–121 (2025). https://doi.org/10.1016/j.jmst.2025.02.011
C. Lei, J. Li, Y. Wu, Y. Xie, Y. Ling et al., Construction of gradient hierarchical and hetero-interfaces structure for ultra-broad microwave absorption. Nano Mater. Sci. 7(2), 249–258 (2025). https://doi.org/10.1016/j.nanoms.2024.04.004
X. Tang, K. Wang, M. Xu, J. Wang, Y. Zhu et al., Temperature-induced impedance gradient polyimide nonwoven fabric for intelligently adjustable broadband microwave absorption. Adv. Funct. Mater. (2026). https://doi.org/10.1002/adfm.74633
G. Feng, L. Guo, H. Yu, Y. Li, B. Ren et al., Uniting superior electromagnetic wave absorption with high thermal stability in bioinspired metamaterial by direct ink writing. Adv. Funct. Mater. 35(36), 2424499 (2025). https://doi.org/10.1002/adfm.202424499
W. Ma, X. Liu, T. Yang, J. Wang, Z. Qiu et al., Strong magnetic–dielectric synergistic gradient metamaterials for boosting superior multispectral ultra-broadband absorption with low-frequency compatibility. Adv. Funct. Mater. 35(18), 2314046 (2025). https://doi.org/10.1002/adfm.202314046
J. Liu, H. Hao, Y. Zhang, L. Wei, Y. Cui et al., Optimizing the electromagnetic wave absorption bandwidth of SiC/C aerogels using continuous multi-band absorption. J. Mater. Chem. A 13(21), 16061–16069 (2025). https://doi.org/10.1039/d5ta01693b
C. Yu, D. Lin, J. Guo, K. Zhuang, Y. Yao et al., Ultralight three-layer gradient-structured MXene/reduced graphene oxide composite aerogels with broadband microwave absorption and dynamic infrared camouflage. Small 20(36), 2401755 (2024). https://doi.org/10.1002/smll.202401755
B. Quan, Y. Wang, Y. Chen, M. Zhang, J. Liu et al., A rational design of multiple-layer films with continuous impedance gradient variation for enhanced microwave absorption. J. Mater. Chem. A. 11(7), 3625–3631 (2023). https://doi.org/10.1039/d2ta08949a
X. Yang, B. Li, B. Lin, H. Wang, T. Zhu et al., Dielectric synergistic gradient metamaterials enable exceptional ultra–wideband microwave absorption and antibacterial properties. Carbon 232, 119813 (2025). https://doi.org/10.1016/j.carbon.2024.119813
L. Guan, M. Du, Q. Liu, Z. Yan, Z. Wang et al., Textile metamaterials for smart adaptive stealth. ACS Nano 19(48), 40677–40702 (2025). https://doi.org/10.1021/acsnano.5c10070
M. Mehari, G. Warrier, A. Dada, A. Kabir, A.P. Haskell-Mendoza et al., Predicting therapeutic clinical trial enrollment for adult patients with low- and high-grade glioma using supervised machine learning. Sci. Adv. 11(23), eadt5708 (2025). https://doi.org/10.1126/sciadv.adt5708
M. Thompson, M. Martín, T.S. Olmo, C. Rajesh, P.K. Koo et al., Massive experimental quantification allows interpretable deep learning of protein aggregation. Sci. Adv. 11(18), eadt5111 (2025). https://doi.org/10.1126/sciadv.adt5111
G. Xu, Z. Zhao, Z.L. Wang, H.-F. Li, Integrating machine learning with triboelectric nanogenerators: optimizing electrode materials and doping strategies for intelligent energy harvesting. Nano Energy 142, 111131 (2025). https://doi.org/10.1016/j.nanoen.2025.111131
Q. Kong, S. Jiang, C. Liufu, J. Cheng, P. Qiu, Robust self-encapsulated fiber integrated with rescue robots for environmental information collection. Nano Energy 141, 111092 (2025). https://doi.org/10.1016/j.nanoen.2025.111092
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