Over 2000‐Fold Current Enhancement via Arc‐Based Triboelectric Nanogenerator at Ultra‐Low Stimulation Speed for Identity Recognition
Feiyu Xie, Maoyi Zhang, Yi-Xiang Wang, C Hu, Tongtong Zhang, Rui Li, YongAn Huang, Bo Wang 等 11 位
Chinese Academy of Sciences Institute of Mechanics University of Chinese Academy of Sciences Beijing Institute of Nanoenergy and Nanosystems
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摘要与影响
Triboelectric nanogenerators (TENGs) are promising energy sources and self‐powered sensors for the Internet of Things, yet the output current strongly depends on mechanical stimulation speed, severely limiting performance under ultra‐low‐speed conditions. Although various strategies have been explored to convert relatively low‐speed mechanical inputs into high‐speed motions, achieving enough current enhancement at ultra‐low stimulation speeds remains a significant challenge. Here, we present an arc‐based triboelectric nanogenerator (A‐TENG) that overcomes this limitation by converting ultra‐low‐speed inputs into high‐speed motions through elastic energy storage and release enabled by an arc structure. The A‐TENG achieves a current enhancement exceeding 2000 fold compared with a conventional vertical contact–separation TENG with planar structures at a stimulation speed of 0.1 mm s −1 . To demonstrate its practical utility, the A‐TENG is implemented as a self‐powered telegraph key for Morse code input and identity recognition. This design strategy provides an effective route for enabling TENGs in ultra‐low‐frequency mechanical energy harvesting and sensing scenarios.
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