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  5. Rationally Structured Triboelectric Nanogenerator Arrays for Harvesting Water‐Current Energy and Self‐Powered Sensing

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Article
en
2022

Rationally Structured Triboelectric Nanogenerator Arrays for Harvesting Water‐Current Energy and Self‐Powered Sensing

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en
2022
Vol 34 (39)
Vol. 34
DOI: 10.1002/adma.202205064

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Zichao Deng
Liang Xu
Huaifang Qin
+4 more

Abstract

Water-current energy is an enormous and widely distributed clean energy in nature, with different scales from large ocean flow to small local turbulence. However, few effective technologies have been proposed to make use of different forms of water currents as a power source. Here, high-performance paired triboelectric nanogenerators (P-TENGs) capable of integrating massively into a thin flexible layer as a structured triboelectric surface (STS) are demonstrated for harvesting water-current energy. Novel gas packet exchange structure and rigid-flexible coupling deformation mechanism are introduced to ensure that the device can work very effectively even in deep water under high water pressure. The rationally designed TENG array in the STS enables highly efficient power take-off from the flow. Typically, the STS demonstrates a high-frequency output up to 57 Hz, largely superior to current TENG devices, and the power density is improved by over 100 times for triboelectric devices harvesting current energy. The flexible STS is capable of attaching to various surfaces or applying independently for self-powered sensing and underwater power supply, showing great potential for water-current energy utilization. Moreover, the work also initiates universal strategies to fabricate high-frequency devices under large environment pressure, which may profoundly enrich the design of TENGs.

How to cite this publication

Zichao Deng, Liang Xu, Huaifang Qin, Xianye Li, Jizhou Duan, Baorong Hou, Zhong Lin Wang (2022). Rationally Structured Triboelectric Nanogenerator Arrays for Harvesting Water‐Current Energy and Self‐Powered Sensing. , 34(39), DOI: https://doi.org/10.1002/adma.202205064.

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Publication Details

Type

Article

Year

2022

Authors

7

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/adma.202205064

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