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  5. High‐Performance Dielectric Elastomer Nanogenerator for Efficient Energy Harvesting and Sensing via Alternative Current Method

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Article
en
2022

High‐Performance Dielectric Elastomer Nanogenerator for Efficient Energy Harvesting and Sensing via Alternative Current Method

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en
2022
Vol 9 (18)
Vol. 9
DOI: 10.1002/advs.202201098

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Zisheng Xu
Kunwei Bao
Kui Di
+10 more

Abstract

Soft, low-cost, high-performance generators are highly desirable for harvesting ambient low frequency mechanical energy. Here, a dielectric elastomer nanogenerator (DENG) is reported, which consists of a dielectric elastomer capacitor, an electret electrostatic voltage source, and a charge pump circuit. Under biaxial stretching, DENG can convert tensile mechanical energy into electrical power without any external power supply. Different from traditional DEG with the charge outward transfer in direct current (DC), the DENG works based on shuttle movement of internal charges in an alternating current (AC). Through alternating current (AC) method, the charge density of the DENG can reach 26 mC m-2 per mechanical cycle, as well as energy density of up to 140 mJ g-1 . Due to the all-solid-state structure without air gap, the DENG is capable of working stably under different ambient humidity (20 RH%-100 RH%). To demonstrate the applications, a water wave harvester based on the DENG is constructed. The integrated device powers a sensing communication module for self-powered remote weather monitoring, showing the potential application in ocean wave energy harvesting.

How to cite this publication

Zisheng Xu, Kunwei Bao, Kui Di, Haojie Chen, Jianbo Tan, Xinjun Xie, Yixin Shao, Jiancheng Cai, Shizhe Lin, Tinghai Cheng, E Shiju, Kang Liu, Zhong Lin Wang (2022). High‐Performance Dielectric Elastomer Nanogenerator for Efficient Energy Harvesting and Sensing via Alternative Current Method. , 9(18), DOI: https://doi.org/10.1002/advs.202201098.

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Publication Details

Type

Article

Year

2022

Authors

13

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/advs.202201098

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