• 文献标题:   A highly stretchable, super-hydrophobic strain sensor based on polydopamine and graphene reinforced nanofiber composite for human motion monitoring
  • 文献类型:   Article
  • 作  者:   LI B, LUO JC, HUANG XW, LIN LW, WANG L, HU MJ, TANG LC, XUE HG, GAO JF, MAI YW
  • 作者关键词:   superhydrophobic, electrically conductive, nanofiber composite, stretchable, wearable strain sensor, human motion monitoring
  • 出版物名称:   COMPOSITES PART BENGINEERING
  • ISSN:   1359-8368 EI 1879-1069
  • 通讯作者地址:   Yangzhou Univ
  • 被引频次:   25
  • DOI:   10.1016/j.compositesb.2019.107580
  • 出版年:   2020

▎ 摘  要

Much attention has been given to flexible electronic devices in recent years. Conductive polymer composites (CPCs) have been utilized to fabricate strain sensors owing to their lightweight and high flexibility. It is a great challenge to develop flexible and wearable strain sensors with light weight, good skin affinity and gas permeability, high sensitivity and excellent corrosion resistance. In this work, electrospun thermoplastic polyurethane (TPU) nanofibers were first decorated by graphene through ultra-sonication, followed by polydopamine (PDA) modification and then hydrophobic treatment with 1H, 1H, 2H, 2H-perfluorodecanethiol (PFDT). The obtained electrical conductive polymer nanofiber composites (CPNCs) have a hierarchical polymer core/graphene shell structure and exhibit super-hydrophobicity even under harsh environments. The introduction of PDA not only improves the interfacial interaction between individual graphene sheets but also the interaction between graphene and the TPU nanofibers. Their mechanical properties including Young's modulus, tensile strength and elongation at break are significantly improved, compared to those of TPU nano-fibrous membranes. When CPNC is used as a strain sensor, it displays high stretchability, controllable sensitivity, excellent cyclical stability and durability. Hence, the nanofiber composite based strain sensor can be attached on the skin for precise monitoring of different human motions, such as tiny and large body movements and thus has promising applications in wearable devices.