• Photonics Research
  • Vol. 10, Issue 5, 1146 (2022)
Ruichao Zhu1, Jiafu Wang1、4、†,*, Jinming Jiang1、5、†,*, Cuilian Xu1, Che Liu2、3, Yuxiang Jia1, Sai Sui1, Zhongtao Zhang1, Tonghao Liu1, Zuntian Chu1, Jun Wang1, Tie Jun Cui2、3、6、†,*, and Shaobo Qu1、7、†,*
Author Affiliations
  • 1Shaanxi Key Laboratory of Artificially-Structured Functional Materials and Devices, Air Force Engineering University, Xi’an 710051, China
  • 2Institute of Electromagnetic Space, Southeast University, Nanjing 210096, China
  • 3State Key Laboratory of Millimeter Wave, Southeast University, Nanjing 210096, China
  • 4e-mail: wangjiafu1981@126.com
  • 5e-mail: 88jiangjinming@163.com
  • 6e-mail: tjcui@seu.edu.cn
  • 7e-mail: qushaobo@mail.xjtu.edu.cn
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    DOI: 10.1364/PRJ.442648 Cite this Article Set citation alerts
    Ruichao Zhu, Jiafu Wang, Jinming Jiang, Cuilian Xu, Che Liu, Yuxiang Jia, Sai Sui, Zhongtao Zhang, Tonghao Liu, Zuntian Chu, Jun Wang, Tie Jun Cui, Shaobo Qu. Machine-learning-empowered multispectral metafilm with reduced radar cross section, low infrared emissivity, and visible transparency[J]. Photonics Research, 2022, 10(5): 1146 Copy Citation Text show less
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    Ruichao Zhu, Jiafu Wang, Jinming Jiang, Cuilian Xu, Che Liu, Yuxiang Jia, Sai Sui, Zhongtao Zhang, Tonghao Liu, Zuntian Chu, Jun Wang, Tie Jun Cui, Shaobo Qu. Machine-learning-empowered multispectral metafilm with reduced radar cross section, low infrared emissivity, and visible transparency[J]. Photonics Research, 2022, 10(5): 1146
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