Interface Defect Detection and Identification of Triboelectric Nanogenerators via Voltage Waveforms and Artificial Neural Network-Reference-Cited by-同舟云学术

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Interface Defect Detection and Identification of Triboelectric Nanogenerators via Voltage Waveforms and Artificial Neural Network

Published:2022-01-10 Issue:2 Volume:14 Page:3437-3445
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Shen Fan¹^ORCID,Li Zhongjie¹²,Xin Chuanfu¹,Guo Hengyu³,Peng Yan¹²^ORCID,Li Kai⁴

Affiliation:

1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, P.R. China

2. School of Artificial Intelligence, Shanghai University, Shanghai 200444, P.R. China

3. Department of Applied Physics, Chongqing University, Chongqing 400044, P. R. China

4. Henan Aerospace Hydraulic & Pneumatic Technology Co., Ltd., Zhengzhou 450000, P.R. China

Funder

Science and Technology Commission of Shanghai Municipality

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.1c19718

Reference45 articles.

1. Theoretical study of contact-mode triboelectric nanogenerators as an effective power source

2. A flutter-effect-based triboelectric nanogenerator for breeze energy collection from arbitrary directions and self-powered wind speed sensor

3. Leaves based triboelectric nanogenerator (TENG) and TENG tree for wind energy harvesting

4. Elasto-Aerodynamics-Driven Triboelectric Nanogenerator for Scavenging Air-Flow Energy

5. Vibration behavior and excitation mechanism of ultra-stretchable triboelectric nanogenerator for wind energy harvesting

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