4.8 Article

Multifunctional and high-performance electronic skin based on silver nanowires bridging graphene

Journal

CARBON
Volume 156, Issue -, Pages 253-260

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.carbon.2019.08.032

Keywords

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Funding

  1. National Key RD Program [2016YFA0200400, 2018YFC2001202]
  2. National Natural Science Foundation of China [61434001, 61574083, 61874065, 51861145202]
  3. National Basic Research Program of China [2015CB352101]
  4. Tsinghua University Tutor Research Fund
  5. Beijing Innovation Center for Future Chip
  6. Beijing Natural Science Foundation [4184091]
  7. Tsinghua-Fuzhou Institute for Date Technology [TFIDT2018008]
  8. Shenzhen Science and Technology Program [JCYJ20150831192224146]
  9. Young Elite Scientists Sponsorship Program by CAST [2018QNRC001]

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Graphene has great potential in the electronic skin to monitor physiological signals. However, many cracks are generated in graphene during the deformation of human body, which would form the open circuit and decrease the measure range, sensitivity, and stability of devices. To solve the problem, we find the answer in higher plant, whose symplasm consists of cytoplasm and plasmodesmata. Cytoplasm is wrapped in hard cell wall like the open circuit of graphene crack. The intercellular communication can only be achieved through plasmodesmata, a nanochannel connecting adjacent cytoplasm. In this article, by imitating the plasmodesmata, a silver nanowires (AgNWs) bridging laser scribed graphene oxide electronic skin (GES) have been proposed with a customized pattern. Compared with the pure GES, the plasmodesmata-like AgNWs bridging GES shows much better performance of mechanical sensitivity and measuring range. Mechanical signals such as pulse, respiration, and joint movement can be detected. In addition, the impedance between GES and skin decreases drastically. More importantly, the excellent matching of the AgNWs bridging GES electrode with the current commercial module facilitates the realtime monitoring of electrocardiogram (ECG) and electroencephalogram (EEG) signals. This work has great potential in the real-time, wearable, and multifunctional physiological monitoring system. (C) 2019 Elsevier Ltd. All rights reserved.

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