Enhanced Strain Sensing Performance of Polymer/Carbon Nanotube-Coated Spandex Fibers via Noncovalent Interactions

被引:30
作者
Chen, Qin [1 ]
Li, Yuntao [1 ]
Xiang, Dong [1 ]
Zheng, Yongfeng [1 ]
Zhu, Wanqiu [1 ]
Zhao, Chunxia [1 ]
Li, Hui [1 ]
Han, Hongchang [1 ]
Shen, Yucai [2 ]
机构
[1] Southwest Petr Univ, Sch Mat Sci & Engn, Chengdu 610500, Sichuan, Peoples R China
[2] Nanjing Tech Univ, Coll Mat Sci & Engn, Nanjing 210009, Jiangsu, Peoples R China
关键词
carbon nanotubes; fibers; nanocomposites; noncovalent interaction; strain sensors; WALLED CARBON NANOTUBES; SENSORS; COMPOSITES; NANOCOMPOSITES; VISUALIZATION; POLYSTYRENE; SENSITIVITY; FABRICATION;
D O I
10.1002/mame.201900525
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Over the past decade, flexible strain sensors have been of tremendous interest due to their wide application in robotics, medical diagnostics, human motion detection, and healthcare. Herein, a fiber strain sensor is fabricated by continuously coating a layer of ultrathin multi-walled carbon nanotube (MWCNT)/thermoplastic polyurethane (TPU) nanocomposites onto the surface of commercial spandex fiber. The effect of noncovalent functionalization of MWCNTs using 1-pyrenecarboxylic acid (PCA) on the electrical conductivity as well as the sensing performance of the fiber sensor is investigated. The low-cost strain sensor possesses a large workable strain (up to 200% strain), high sensitivity (gauge factor is 14 191.5 under 170-200% strain), and excellent stability (up to 1000 cycles), and regular signal responses within a wide measuring frequency range of 0.01-1 Hz are achieved with the introduction of PCA via enhanced nanotube dispersion and polymer-nanofiller interactions. Additionally, the resistance response to strain is fitted with a model based on tunneling theory to understand the sensing mechanism, and to prove that the fitted results are in agreement with the experimental results. Furthermore, the developed sensor is successfully applied in human motion detection, such as joint movement, facial microexpressions, and speech recognition.
引用
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页数:10
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