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  5. Multilayered Helical Spherical Triboelectric Nanogenerator with Charge Shuttling for Water Wave Energy Harvesting

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Article
en
2023

Multilayered Helical Spherical Triboelectric Nanogenerator with Charge Shuttling for Water Wave Energy Harvesting

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en
2023
Vol 7 (3)
Vol. 7
DOI: 10.1002/smtd.202201392

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Shijie Liu
Xi Liang
Pengfei Chen
+3 more

Abstract

As an important part of natural resources, islands support the marine economy and build a blue barrier for marine ecological civilization. However, the power supply on these islands is difficult, limiting the development of marine internet of things (IoTs). In order to break the status quo, this work applies triboelectric nanogenerators (TENGs) to island power supply and ecological monitoring. A spherical TENG with two multilayered helical units is designed to harvest water wave energy, in which the space utilization rate reaches 92.5%. Then a charge shuttling mechanism is developed to improve the electrical output. The output current and power of a single TENG without power management reach 200.3 µA and 16.2 mW respectively, corresponding to a peak power density of 23.2 W m-3 . Moreover, a scheme of the power managed TENG is proposed for realizing large-scale wave energy harvesting. The TENG is demonstrated to successfully power a water quality detector, a Bluetooth thermo-hygrometer, and an intelligent wireless alarm system for remote environmental monitoring. This work not only proposes a new type of TENG for water wave energy harvesting with improved performance, but also provides a new strategy for intelligent ocean IoTs, which even contributes to the carbon neutralization.

How to cite this publication

Shijie Liu, Xi Liang, Pengfei Chen, Hairong Long, Tao Jiang, Zhong Lin Wang (2023). Multilayered Helical Spherical Triboelectric Nanogenerator with Charge Shuttling for Water Wave Energy Harvesting. , 7(3), DOI: https://doi.org/10.1002/smtd.202201392.

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Publication Details

Type

Article

Year

2023

Authors

6

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/smtd.202201392

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