4.7 Article

Knitted Ti3C2Tx MXene based fiber strain sensor for human-computer interaction

Journal

JOURNAL OF COLLOID AND INTERFACE SCIENCE
Volume 604, Issue -, Pages 643-649

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcis.2021.07.025

Keywords

MXene; Strain sensor; Fiber electronics; Human-computer interaction; Data glove

Funding

  1. National Natural Science Foundation of China (NSFC) [21571080, 51502110]

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The fiber strain sensor developed based on Ti3C2Tx@P(VDF-TrFE) polymer nanofibers prepared via electrostatic spinning exhibits high gauge factor, rapid response, and outstanding durability, enabling real-time monitoring of human motions and physiological signals, and is suitable for wearable electronic devices.
Fiber-based stretchable electronics with feasibility of weaving into textiles and advantages of light-weight, long-term stability, conformability and easy integration are highly desirable for wearable electronics to realize personalized medicine, artificial intelligence and human health monitoring. Herein, a fiber strain sensor is developed based on the Ti3C2Tx MXene wrapped by poly(vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) polymer nanofibers prepared via electrostatic spinning. Owing to the good conductivity of Ti3C2Tx and unique 3D reticular structure with wave shape, the resistance of Ti3C2Tx@P(VDF-TrFE) polymer nanofibers changes under external force, thus providing remarkable strain inducted sensing performance. As-fabricated sensor exhibits high gauge factor (GF) of 108.8 in range of 45-66% strain, rapid response of 19 ms, and outstanding durability over 1600 stretching/releasing cycles. The strain sensor is able to monitor vigorous human motions (finger or wrist bending) and subtle physiological signals (blinking, pulse or voice recognition) in real-time. Moreover, a data glove is designed to connect different gestures and expressions to form an intelligent gesture-expression control system, further confirming the practicability of our Ti3C2Tx@P(VDF-TrFE) strain sensors in multifunctional wearable electronic devices. (C) 2021 Elsevier Inc. All rights reserved.

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