4.6 Article

Customizable Textile Sensors Based on Helical Core-Spun Yarns for Seamless Smart Garments

期刊

LANGMUIR
卷 37, 期 10, 页码 3122-3129

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.langmuir.0c03595

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资金

  1. National Natural Science Foundation of China [51672141]
  2. Natural Science Foundation of Shandong Province of China [ZR2018QEM004]
  3. Shandong Province Key Research and Development Plan [2019JZZY010340, 2019JZZY010335, 2019GGXI02022]
  4. Anhui Province Special Science and Technology Project [201903a05020028]
  5. Shandong Provincial Universities Youth Innovation Technology Plan Innovation Team [2020KJA013]
  6. State Key Laboratory of Bio-Fibers and Eco-Textiles (Qingdao University) [ZKT02]

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A smart textile sensor with graphene-based conductive core-spun yarns was developed, showing high elasticity, fast response time, wide sensing range, and low detection limit for monitoring limb movement and physiological signals. This seamless smart textile fabric has great potential for real-time precise medicine and healthcare applications.
Most of the current sensors cannot meet the needs for seamless integration into the textile substrates of smart clothing and require improvements in terms of comfort and durability. Herein, smart textile-based sensors that have different sensing properties with integrated electronic elements were fabricated by knitting graphene-based helical conductive core-spun yarns. Such graphene-modified core-spun yarns are employed as building blocks of textile strain sensors, which showed high elasticity (epsilon > 300%), fast response time (120 ms), excellent reproducibility (over 10 000 cycles), wide sensing range (up to 100% strain), and low detection limit (0.3% strain). Thus, resistance-type strain sensors and capacitance-type pressure sensors composed of graphene-based smart fabric could be used to monitor large-scale limb movement and subtle human physiological signals. Such seamless smart textile-based fabric composed of superelastic helical conductive core-spun yarns shows great potential for fabricating an intelligent device to achieve real-time precise medicine and healthcare.

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