4.7 Article

A Flexible TENG Based on Micro-Structure Film for Speed Skating Techniques Monitoring and Biomechanical Energy Harvesting

期刊

NANOMATERIALS
卷 12, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/nano12091576

关键词

self-powered; wearable flexible sensor; energy harvesting; human motion monitoring; triboelectric nanogenerator

资金

  1. Research and demonstration on key technologies of National Scientific Training Base Construction [2018YFF0300806]
  2. Winter Sports Training monitoring technical services [2020021300002]

向作者/读者索取更多资源

This paper introduces a self-powered and portable micro-structure triboelectric nanogenerator (MS-TENG) with outstanding sensing properties and the capability to store biomechanical energy. The generator has great application potential in human sports training monitoring and big data analysis.
Wearable motion-monitoring systems have been widely used in recent years. However, the battery energy storage problem of traditional wearable devices limits the development of human sports training applications. In this paper, a self-powered and portable micro-structure triboelectric nanogenerator (MS-TENG) has been made. It consists of micro-structure polydimethylsiloxane (PDMS) film, fluorinated ethylene propylene (FEP) film, and lithium chloride polyacrylamide (LiCl-PAAM) hydrogel. Through the micro-structure, the voltage of the MS-TENG can be improved by 7 times. The MS-TENG provides outstanding sensing properties: maximum output voltage of 74 V, angular sensitivity of 1.016 V/degree, high signal-to-noise ratio, and excellent long-term service stability. We used it to monitor the running skills of speed skaters. It can also store the biomechanical energy which is generated in the process of speed skating through capacitors. It demonstrates capability of sensor to power electronic calculator and electronic watch. In addition, as a flexible electrode hydrogel, it can readily stretch over 1300%, which can help improve the service life and work stability of MS-TENG. Therefore, MS-TENG has great application potential in human sports training monitoring and big data analysis.

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