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Design of flexible micro-porous fiber with double conductive network synergy for high-performance strain sensor.

Authors :
Wang, Xiaozheng
Zhao, Xinxin
Yu, Yunfei
Zhai, Wei
Yue, Xiaoyan
Dai, Kun
Liu, Chuntai
Shen, Changyu
Source :
Chemical Engineering Journal. Sep2024, Vol. 495, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

[Display omitted] • A core-sheath composite fiber based on TPU and MWCNTs is obtained by wet spinning. • The unique dual conductive network structure is constructed by MWCNTs and RGO. • The"shoulder-peak" phenomenon is effectively weakened due to the dual conductive network structure. • The fiber-shaped strain sensor shows good response behavior in monitoring human motions. Flexible wearable strain sensor is a vital part of intelligent wearable systems due to their broad applications in human–machine interaction and smart clothes. Flexible strain sensor fabricated via conventional blending conductive polymer composites has some drawbacks, for example, low sensitivity, large hysteresis, and "shoulder-peak" phenomenon, which limit their practical applications greatly. Herein, we prepared a fiber-shaped strain sensor with a micro-porous, three-layer structure together with a dual conductive network based on reduced graphene oxide (rGO) and multi-walled carbon nanotubes (MWCNTs). The strain sensor demonstrates excellent response behaviors, including splendid stretchability (686 %), wide detection range (120 %), high sensitivity (gauge factor = 300), fast response time (300 ms) and excellent durability (over 9000 cycles). The unique dual conductive network structure endows the strain sensor with remarkable recoverability and reproducibility. The resistance of the strain sensor can recover to nearly initial conditions after the releasing process, exhibiting lower hysteresis. The "shoulder-peak" phenomenon has also been weakened based on the microstructure and conductive network design. Based on the high sensitivity and excellent response behavior, the fiber-shaped strain sensor performs real-time monitoring of breathing, finger bending, walking, and other human motions, providing a good candidate for its application in intelligent wearable devices. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13858947
Volume :
495
Database :
Academic Search Index
Journal :
Chemical Engineering Journal
Publication Type :
Academic Journal
Accession number :
178975603
Full Text :
https://doi.org/10.1016/j.cej.2024.153641