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A non-printed integrated-circuit textile for wireless theranostics

Author

Listed:
  • Yuxin Yang

    (Chongqing University
    Chinese Academy of Sciences
    Industrial Technology Research Institute of Chongqing University)

  • Xiaofei Wei

    (Chongqing University)

  • Nannan Zhang

    (Chongqing University)

  • Juanjuan Zheng

    (Harvard University)

  • Xing Chen

    (Harvard University)

  • Qian Wen

    (Chongqing University
    Industrial Technology Research Institute of Chongqing University)

  • Xinxin Luo

    (Industrial Technology Research Institute of Chongqing University)

  • Chong-Yew Lee

    (University Sains Malaysia)

  • Xiaohong Liu

    (Chinese Academy of Sciences)

  • Xingcai Zhang

    (Harvard University
    Massachusetts Institute of Technology)

  • Jun Chen

    (University of California, Los Angeles)

  • Changyuan Tao

    (Chongqing University)

  • Wei Zhang

    (Chinese Academy of Sciences)

  • Xing Fan

    (Chongqing University
    Industrial Technology Research Institute of Chongqing University)

Abstract

While the printed circuit board (PCB) has been widely considered as the building block of integrated electronics, the world is switching to pursue new ways of merging integrated electronic circuits with textiles to create flexible and wearable devices. Herein, as an alternative for PCB, we described a non-printed integrated-circuit textile (NIT) for biomedical and theranostic application via a weaving method. All the devices are built as fibers or interlaced nodes and woven into a deformable textile integrated circuit. Built on an electrochemical gating principle, the fiber-woven-type transistors exhibit superior bending or stretching robustness, and were woven as a textile logical computing module to distinguish different emergencies. A fiber-type sweat sensor was woven with strain and light sensors fibers for simultaneously monitoring body health and the environment. With a photo-rechargeable energy textile based on a detailed power consumption analysis, the woven circuit textile is completely self-powered and capable of both wireless biomedical monitoring and early warning. The NIT could be used as a 24/7 private AI “nurse” for routine healthcare, diabetes monitoring, or emergencies such as hypoglycemia, metabolic alkalosis, and even COVID-19 patient care, a potential future on-body AI hardware and possibly a forerunner to fabric-like computers.

Suggested Citation

  • Yuxin Yang & Xiaofei Wei & Nannan Zhang & Juanjuan Zheng & Xing Chen & Qian Wen & Xinxin Luo & Chong-Yew Lee & Xiaohong Liu & Xingcai Zhang & Jun Chen & Changyuan Tao & Wei Zhang & Xing Fan, 2021. "A non-printed integrated-circuit textile for wireless theranostics," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25075-8
    DOI: 10.1038/s41467-021-25075-8
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    Cited by:

    1. Bangfeng Wang & Yiwei Li & Mengfan Zhou & Yulong Han & Mingyu Zhang & Zhaolong Gao & Zetai Liu & Peng Chen & Wei Du & Xingcai Zhang & Xiaojun Feng & Bi-Feng Liu, 2023. "Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Ziqi Qu & Zhechen Zhu & Yulong Liu & Mengxia Yu & Terry Tao Ye, 2023. "Parasitic capacitance modeling and measurements of conductive yarns for e-textile devices," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Shaomei Lin & Weifeng Yang & Xubin Zhu & Yubin Lan & Kerui Li & Qinghong Zhang & Yaogang Li & Chengyi Hou & Hongzhi Wang, 2024. "Triboelectric micro-flexure-sensitive fiber electronics," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    4. Pengwei Wang & Xiaohao Ma & Zhiqiang Lin & Fan Chen & Zijian Chen & Hong Hu & Hailong Xu & Xinyi Zhang & Yuqing Shi & Qiyao Huang & Yuanjing Lin & Zijian Zheng, 2024. "Well-defined in-textile photolithography towards permeable textile electronics," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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