Triboelectric nanogenerator based on well-dispersed and oxide-free liquid metal-doped conductive hydrogel as self-powered wearable sensor for respiratory and thyroid cartilage signal monitoring

被引:0
|
作者
Yang, Qiannian [1 ]
Yu, Maolin [1 ]
Zhang, Hongyi [1 ]
Li, Na [1 ]
Du, Jingjing [1 ]
Xu, Lijian [1 ]
Xu, Jianxiong [1 ]
机构
[1] Hunan Univ Technol, Coll Life Sci & Chem, Hunan Key Lab Biomed Nanomat & Devices, Zhuzhou 412007, Peoples R China
基金
湖南省自然科学基金; 中国国家自然科学基金;
关键词
Conductive hydrogel; Liquid metal; Triboelectric nanogenerators; Self-powered sensor; Energy supply device;
D O I
10.1016/j.nanoen.2024.110530
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The poor dispersibility and easy surface oxidation of liquid metal (LM) significantly reduce the conductivity, mechanical property and stability of the composite hydrogels, thereby affecting their sensing performance. Herein, a well-dispersed and oxide-free LM-doped conductive double network (DN) hydrogel (CMC/P(AA-coDAC)/NaCl-LM) is successfully prepared by employing bio-macromolecules (carboxymethyl cellulose (CMC) and double-bond functionalized CMC (CMC-AGE crosslinker) encapsulated oxide-free LM droplet at acidic condition as the first network and poly(acrylic acid-co-acryloyloxyethyltrimethyl ammonium chloride) (P(AA-co-DAC)) as the second network under the presence of NaCl. In this hydrogel, the multiple interactions and the synergistic effect between two interpenetrating networks insures multifunctional features of the hydrogels. As a result, the composite hydrogel exhibits superior mechanical properties (stress of 389.81 kPa and strain of 2866.44 %) and high conductivity (5.27 S/m). Subsequently, a triboelectric nanogenerator (CPL-TENG) is constructed using the composite hydrogel as electrode material, which displayed an excellent electrical out performance (V-OC of 223.32 V, I-SC of 9.78 mu A, Q(SC) of 82.33 nC, and power density of 4.30 W/m(2)) and highly-sensitive (pressure sensitivity of 0.268 kPa(-1)). Eventually, the as-fabricated CPL-TENG as a self-powered sensor for respiratory signal monitoring and machine learning-assisted language recognition is described and its great potential in wearable electronics and energy supply devices is foreseen.
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页数:14
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