Issue 1, 2018

Design of a wearable and shape-memory fibriform sensor for the detection of multimodal deformation

Abstract

A wearable and shape-memory strain sensor with a coaxial configuration is designed, comprising a thermoplastic polyurethane fiber as the core support, well-aligned and interconnected carbon nanotubes (CNTs) as conductive filaments, and polypyrrole (PPy) coating as the cladding layer. In this design, the stress relaxation between CNTs is well confined by the outer PPy cladding layer, which endows the fibriform sensor with good reliability and repeatability. The microcracks generated when the coaxial fiber is under strain guarantee the superior sensitivity of this fibriform sensor with a gauge factor of 12 at 0.1% strain, a wide detectable range (from 0.1% to 50% tensile strain), and the ability to detect multimodal deformation (tension, bending, and torsion) and human motions (finger bending, breathing, and phonation). In addition, due to its shape-memory characteristic, the sensing performance of the fibriform sensor is well retained after its shape recovers from 50% deformation and the fabric woven from the shape-memory coaxial fibers can be worn on the elbow joints in a reversible manner (original-enlarged-recovered) and fitted tightly. Thus, this sensor shows promising applications in wearable electronics.

Graphical abstract: Design of a wearable and shape-memory fibriform sensor for the detection of multimodal deformation

Supplementary files

Article information

Article type
Communication
Submitted
21 Aug 2017
Accepted
21 Nov 2017
First published
22 Nov 2017

Nanoscale, 2018,10, 118-123

Design of a wearable and shape-memory fibriform sensor for the detection of multimodal deformation

L. Li, P. Shi, L. Hua, J. An, Y. Gong, R. Chen, C. Yu, W. Hua, F. Xiu, J. Zhou, G. Gao, Z. Jin, G. Sun and W. Huang, Nanoscale, 2018, 10, 118 DOI: 10.1039/C7NR06219B

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