Flexible and durable wood-based triboelectric nanogenerators for self-powered sensing in athletic big data analytics
Jianjun Luo, Ziming Wang, Ziming Wang, Liang Xu, Aurelia Chi Wang, Kai Han, Tao Jiang, Yu Bai 等 13 位
Chinese Academy of Sciences Beijing Institute of Nanoenergy and Nanosystems University of Chinese Academy of Sciences Georgia Institute of Technology
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摘要与影响
In the new era of internet of things, big data collection and analysis based on widely distributed intelligent sensing technology is particularly important. Here, we report a flexible and durable wood-based triboelectric nanogenerator for self-powered sensing in athletic big data analytics. Based on a simple and effective strategy, natural wood can be converted into a high-performance triboelectric material with excellent mechanical properties, such as 7.5-fold enhancement in strength, superior flexibility, wear resistance and processability. The electrical output performance is also enhanced by more than 70% compared with natural wood. A self-powered falling point distribution statistical system and an edge ball judgement system are further developed to provide training guidance and real-time competition assistance for both athletes and referees. This work can not only expand the application area of the self-powered system to smart sport monitoring and assisting, but also promote the development of big data analytics in intelligent sports industry.
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工程Advanced Sensor and Energy Harvesting Materials
Conducting polymers and applications · Innovative Energy Harvesting Technologies
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