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  5. Leaf‐Like TENGs for Harvesting Gentle Wind Energy at An Air Velocity as Low as 0.2 m s<sup>−1</sup>

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Article
en
2023

Leaf‐Like TENGs for Harvesting Gentle Wind Energy at An Air Velocity as Low as 0.2 m s<sup>−1</sup>

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en
2023
Vol 33 (11)
Vol. 33
DOI: 10.1002/adfm.202212207

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Hao Li
Jing Wen
Zhiqiang Ou
+6 more

Abstract

Abstract Existing technologies for harvesting electrical energy from gentle wind face an enormous challenge due to the limitations of cut‐in and rated wind speed. Here, a leaf‐like triboelectric nanogenerator (LL‐TENG) is proposed that uses contact electrification caused by the damped forced vibration of topology‐optimized structure consisting of flexible leaf, vein bearing plate, and counterweight piece. The effectiveness of the topology‐optimized leaf‐like structure is studied, which solves the problem of reduced output due to electrostatic adsorption between the leaf surfaces while reducing the cut‐in (0.2 m s −1 ) and rated wind speed (2.5 m s −1 ). The LL‐TENG unit having small dimensions of 40 cm −2 (mass of 9.7 g) at a gentle wind of 2.5 m s −1 exhibits outstanding electrical performances, which produces an open‐circuit voltage of 338 V, a short‐circuit current of 7.9 µA and the transferred charge density of 62.5 µC m −2 with a low resonant frequency of 4 Hz, giving an instantaneous peak power of 2 mW. A distributed power source consists of the five LL‐TENGs in parallel is developed by designed self‐adaptive structure, for which the peak power output reaches 3.98 mW, and its practicability and durability are successfully demonstrated. This study is a promising distributed power source technology to drive electronics in gentle wind outdoor environments.

How to cite this publication

Hao Li, Jing Wen, Zhiqiang Ou, Erming Su, Fangjing Xing, Yuhan Yang, Yanshuo Sun, Zhong Lin Wang, Baodong Chen (2023). Leaf‐Like TENGs for Harvesting Gentle Wind Energy at An Air Velocity as Low as 0.2 m s<sup>−1</sup>. , 33(11), DOI: https://doi.org/10.1002/adfm.202212207.

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Publication Details

Type

Article

Year

2023

Authors

9

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/adfm.202212207

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