IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-58249-9.html
   My bibliography  Save this article

Flexible intelligent microwave metasurface with shape-guided adaptive programming

Author

Listed:
  • Fan Li

    (University of Electronic Science and Technology of China)

  • Taisong Pan

    (University of Electronic Science and Technology of China)

  • Weihan Li

    (Southeast University)

  • Zujun Peng

    (Institute of Flexible Electronics Technology of THU)

  • Dengji Guo

    (University of Electronic Science and Technology of China)

  • Xiang Jia

    (University of Electronic Science and Technology of China)

  • Taiqi Hu

    (University of Electronic Science and Technology of China)

  • Lingxiao Wang

    (University of Electronic Science and Technology of China)

  • Wei Wang

    (Institute of Flexible Electronics Technology of THU)

  • Min Gao

    (University of Electronic Science and Technology of China)

  • Guang Yao

    (University of Electronic Science and Technology of China)

  • Le Zuo

    (The 29th Research Institute of China Electronics Technology Group Corporation)

  • Mei Bi

    (University of Electronic Science and Technology of China)

  • Xiaolong Weng

    (University of Electronic Science and Technology of China)

  • Wenxuan Tang

    (Southeast University)

  • Yuan Lin

    (University of Electronic Science and Technology of China
    University of Electronic Science and Technology of China
    University of Electronic Science and Technology of China)

Abstract

Empowering the reconfigurable metasurfaces (RM) with the capability to be mechanically deformable highlights the possibility to manipulate the electromagnetic (EM) wave across arbitrary surfaces. Such ambition is hampered by the absence of adaptivity to shape variation in current programming strategies for RM. Herein, we present a flexible intelligent surface platform (FISP) as a solution to achieve flexible RM with highly stable performance under dynamic deformation. The geometry acquisition module in FISP enables real-time awareness of RM’s deformation with the conformal sensor array. By merging the actual shape of flexible RM into the input of the adaptive algorithm driven by the artificial neural network, the deformed flexible RM in FISP can be autonomously encoded by the bias voltage supply module to ensure robust performance under various deformation conditions. The versatility of FISP in manipulating EM waves is demonstrated by its applications in electromagnetic illusion, carpet cloaking, and data transmission, illustrating the prospects for seamlessly integrating flexible electronics and RM in the development of future EM metasurfaces.

Suggested Citation

  • Fan Li & Taisong Pan & Weihan Li & Zujun Peng & Dengji Guo & Xiang Jia & Taiqi Hu & Lingxiao Wang & Wei Wang & Min Gao & Guang Yao & Le Zuo & Mei Bi & Xiaolong Weng & Wenxuan Tang & Yuan Lin, 2025. "Flexible intelligent microwave metasurface with shape-guided adaptive programming," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58249-9
    DOI: 10.1038/s41467-025-58249-9
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-58249-9
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-025-58249-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Seyedeh Mahsa Kamali & Amir Arbabi & Ehsan Arbabi & Yu Horie & Andrei Faraon, 2016. "Decoupling optical function and geometrical form using conformal flexible dielectric metasurfaces," Nature Communications, Nature, vol. 7(1), pages 1-7, September.
    2. Si Ran Wang & Jun Yan Dai & Qun Yan Zhou & Jun Chen Ke & Qiang Cheng & Tie Jun Cui, 2023. "Manipulations of multi-frequency waves and signals via multi-partition asynchronous space-time-coding digital metasurface," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    3. Lianlin Li & Hengxin Ruan & Che Liu & Ying Li & Ya Shuang & Andrea Alù & Cheng-Wei Qiu & Tie Jun Cui, 2019. "Machine-learning reprogrammable metasurface imager," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    4. Lianlin Li & Tie Jun Cui & Wei Ji & Shuo Liu & Jun Ding & Xiang Wan & Yun Bo Li & Menghua Jiang & Cheng-Wei Qiu & Shuang Zhang, 2017. "Electromagnetic reprogrammable coding-metasurface holograms," Nature Communications, Nature, vol. 8(1), pages 1-7, December.
    5. Kedi Wu & Philippe Coquet & Qi Jie Wang & Patrice Genevet, 2018. "Modelling of free-form conformal metasurfaces," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    6. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    7. Weihan Li & Qian Ma & Che Liu & Yunfeng Zhang & Xianning Wu & Jiawei Wang & Shizhao Gao & Tianshuo Qiu & Tonghao Liu & Qiang Xiao & Jiaxuan Wei & Ting Ting Gu & Zhize Zhou & Fashuai Li & Qiang Cheng &, 2023. "Intelligent metasurface system for automatic tracking of moving targets and wireless communications based on computer vision," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenzhi Li & Qiyue Yu & Jing Hui Qiu & Jiaran Qi, 2024. "Intelligent wireless power transfer via a 2-bit compact reconfigurable transmissive-metasurface-based router," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Xin Wang & Jia Qi Han & Guan Xuan Li & De Xiao Xia & Ming Yang Chang & Xiang Jin Ma & Hao Xue & Peng Xu & Rui Jie Li & Kun Yi Zhang & Hai Xia Liu & Long Li & Tie Jun Cui, 2023. "High-performance cost efficient simultaneous wireless information and power transfers deploying jointly modulated amplifying programmable metasurface," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Tianshuo Qiu & Qiang An & Jianqi Wang & Jiafu Wang & Cheng-Wei Qiu & Shiyong Li & Hao Lv & Ming Cai & Jianyi Wang & Lin Cong & Shaobo Qu, 2024. "Vision-driven metasurfaces for perception enhancement," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    4. De Xiao Xia & Jia Qi Han & Ya Jie Mu & Lei Guan & Xin Wang & Xiang Jin Ma & Li Hao Zhu & Tian Guang Lv & Hai Xia Liu & Yan Shi & Long Li & Tie Jun Cui, 2024. "Adaptive wireless-powered network based on CNN near-field positioning by a dual-band metasurface," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Erda Wen & Xiaozhen Yang & Daniel F. Sievenpiper, 2023. "Real-data-driven real-time reconfigurable microwave reflective surface," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    6. Liheng Bian & Daoyu Li & Shuoguang Wang & Chunyang Teng & Jinxuan Wu & Huteng Liu & Hanwen Xu & Xuyang Chang & Guoqiang Zhao & Shiyong Li & Jun Zhang, 2024. "Towards large-scale single-shot millimeter-wave imaging for low-cost security inspection," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    7. Xiao Qing Chen & Lei Zhang & Yi Ning Zheng & Shuo Liu & Zhuo Ran Huang & Jing Cheng Liang & Marco Renzo & Vincenzo Galdi & Tie Jun Cui, 2025. "Integrated sensing and communication based on space-time-coding metasurfaces," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    8. Huan Lu & Jiwei Zhao & Bin Zheng & Chao Qian & Tong Cai & Erping Li & Hongsheng Chen, 2023. "Eye accommodation-inspired neuro-metasurface focusing," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
    9. Weihan Li & Qian Ma & Che Liu & Yunfeng Zhang & Xianning Wu & Jiawei Wang & Shizhao Gao & Tianshuo Qiu & Tonghao Liu & Qiang Xiao & Jiaxuan Wei & Ting Ting Gu & Zhize Zhou & Fashuai Li & Qiang Cheng &, 2023. "Intelligent metasurface system for automatic tracking of moving targets and wireless communications based on computer vision," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    10. Tulika Saha & Sriparna Saha & Pushpak Bhattacharyya, 2020. "Towards sentiment aided dialogue policy learning for multi-intent conversations using hierarchical reinforcement learning," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-28, July.
    11. Mahmoud Mahfouz & Angelos Filos & Cyrine Chtourou & Joshua Lockhart & Samuel Assefa & Manuela Veloso & Danilo Mandic & Tucker Balch, 2019. "On the Importance of Opponent Modeling in Auction Markets," Papers 1911.12816, arXiv.org.
    12. Lixiang Zhang & Yan Yan & Yaoguang Hu, 2024. "Deep reinforcement learning for dynamic scheduling of energy-efficient automated guided vehicles," Journal of Intelligent Manufacturing, Springer, vol. 35(8), pages 3875-3888, December.
    13. Benjamin Heinbach & Peter Burggräf & Johannes Wagner, 2024. "gym-flp: A Python Package for Training Reinforcement Learning Algorithms on Facility Layout Problems," SN Operations Research Forum, Springer, vol. 5(1), pages 1-26, March.
    14. Woo Jae Byun & Bumkyu Choi & Seongmin Kim & Joohyun Jo, 2023. "Practical Application of Deep Reinforcement Learning to Optimal Trade Execution," FinTech, MDPI, vol. 2(3), pages 1-16, June.
    15. Lu, Yu & Xiang, Yue & Huang, Yuan & Yu, Bin & Weng, Liguo & Liu, Junyong, 2023. "Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load," Energy, Elsevier, vol. 271(C).
    16. Yuhong Wang & Lei Chen & Hong Zhou & Xu Zhou & Zongsheng Zheng & Qi Zeng & Li Jiang & Liang Lu, 2021. "Flexible Transmission Network Expansion Planning Based on DQN Algorithm," Energies, MDPI, vol. 14(7), pages 1-21, April.
    17. Pedro Reis & Ana Paula Serra & Jo~ao Gama, 2025. "The Role of Deep Learning in Financial Asset Management: A Systematic Review," Papers 2503.01591, arXiv.org.
    18. Michelle M. LaMar, 2018. "Markov Decision Process Measurement Model," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 67-88, March.
    19. Yang, Ting & Zhao, Liyuan & Li, Wei & Zomaya, Albert Y., 2021. "Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning," Energy, Elsevier, vol. 235(C).
    20. Wang, Yi & Qiu, Dawei & Sun, Mingyang & Strbac, Goran & Gao, Zhiwei, 2023. "Secure energy management of multi-energy microgrid: A physical-informed safe reinforcement learning approach," Applied Energy, Elsevier, vol. 335(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58249-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.