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  5. Achieving a Large Driving Force on Triboelectric Nanogenerator by Wave‐Driven Linkage Mechanism for Harvesting Blue Energy toward Marine Environment Monitoring

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Article
en
2022

Achieving a Large Driving Force on Triboelectric Nanogenerator by Wave‐Driven Linkage Mechanism for Harvesting Blue Energy toward Marine Environment Monitoring

0 Datasets

0 Files

en
2022
Vol 13 (5)
Vol. 13
DOI: 10.1002/aenm.202203219

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Jiajia Han
Yuan Liu
Yawei Feng
+2 more

Abstract

Abstract Water wave energy is regarded to be a promising renewable energy source to relieve the pressure of fossil energy shortage and achieve a sustainable future. A cylindrical wave‐driven linkage mechanism triboelectric nanogenerator (WLM‐TENG) with unidirectional rotation is designed and fabricated to effectively harvest water wave energy. The enormous force generated by water waves, which is up to 424.3 N m −2 , is used to drive the TENG through its simple and smart mechanical structure. This force allows the rotor to overcome the large resistance caused by the full contact between rabbit furs and electrodes. The output current can reach about 30 µA and the output power arrives at 50 mW. Moreover, self‐powered applications powered by the WLM‐TENG are successfully demonstrated, including indicating light‐emitting diodes (LEDs), multifunctional barometer, portable anemometer, and multifunctional water quality detection pen. This work renders an effective approach to harness the enormous force generated by the water waves, enhancing the water wave energy harvesting ability of the TENG, toward practical applications of marine environment monitoring.

How to cite this publication

Jiajia Han, Yuan Liu, Yawei Feng, Tao Jiang, Zhong Lin Wang (2022). Achieving a Large Driving Force on Triboelectric Nanogenerator by Wave‐Driven Linkage Mechanism for Harvesting Blue Energy toward Marine Environment Monitoring. , 13(5), DOI: https://doi.org/10.1002/aenm.202203219.

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Publication Details

Type

Article

Year

2022

Authors

5

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/aenm.202203219

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