Gu Mengxi, Zhou Xuan, Shen Jienan, Xie Ruibin, Su Yuhan, Gao Junxue, Zhao Binzhe, Li Jie, Duan Yingjie, Wang Zhixun, Hu Yougen, Gu Guoqiang, Wang Lei, Wei Lei, Yang Chunlei, Chen Ming
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, People's Republic of China.
University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China.
iScience. 2024 Mar 11;27(4):109481. doi: 10.1016/j.isci.2024.109481. eCollection 2024 Apr 19.
It is still a great challenge for the flexible piezoresistive pressure sensors to simultaneously achieve wide linearity and high sensitivity. Herein, we propose a high-performance textile pressure sensor based on chitosan (CTS)/MXene fiber. The hierarchical "point to line" architecture enables the pressure sensor with high sensitivity of 1.16 kPa over an ultrawide linear range of 1.5 MPa. Furthermore, the CTS/MXene pressure sensor possesses a low fatigue over 1000 loading/unloading cycles under 1.5 MPa pressure load, attributed to the strong chemical bonding between CTS fiber and MXene and excellent mechanical stability. Besides, the proposed sensor shows good antibacterial effect benefiting from the strong interaction between polycationic structure of CTS/MXene and the predominantly anionic components of bacteria surface. The sensor is also applied to detect real-time human action, an overall classification accuracy of 98.61% based on deep neural network-convolutional neural network (CNN) for six human actions is realized.
对于柔性压阻式压力传感器而言，要同时实现宽线性度和高灵敏度仍然是一个巨大的挑战。在此，我们提出了一种基于壳聚糖（CTS）/MXene纤维的高性能纺织压力传感器。这种分层的“点到线”结构使压力传感器在1.5 MPa的超宽线性范围内具有1.16 kPa的高灵敏度。此外，CTS/MXene压力传感器在1.5 MPa压力负载下经过1000次加载/卸载循环后具有低疲劳性，这归因于CTS纤维与MXene之间的强化学键合以及出色的机械稳定性。此外，所提出的传感器由于CTS/MXene的聚阳离子结构与细菌表面主要阴离子成分之间的强相互作用而显示出良好的抗菌效果。该传感器还被应用于检测实时人体动作，基于深度神经网络-卷积神经网络（CNN）对六种人体动作实现了98.61%的总体分类准确率。
