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Triboelectric nanogenerator based self-powered sensor for artificial intelligence

Yuankai Zhou, Maoliang Shen, Xin Cui, Yicheng Shao, Lijie Li Orcid Logo, Yan Zhang

Nano Energy, Volume: 84, Start page: 105887

Swansea University Author: Lijie Li Orcid Logo

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DOI (Published version): 10.1016/j.nanoen.2021.105887

Abstract

Triboelectric nanogenerator based sensor has excellent material compatibility, low cost, and flexibility, which is a unique candidate technology for artificial intelligence. Triboelectric nanogenerators effectively provide critical infrastructure for new generation of sensing systems that collect in...

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Published in: Nano Energy
ISSN: 2211-2855
Published: Elsevier BV 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa56257
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first_indexed 2021-02-16T13:36:33Z
last_indexed 2021-02-27T04:20:18Z
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spelling 2021-02-26T14:14:16.0117870 v2 56257 2021-02-15 Triboelectric nanogenerator based self-powered sensor for artificial intelligence ed2c658b77679a28e4c1dcf95af06bd6 0000-0003-4630-7692 Lijie Li Lijie Li true false 2021-02-15 EEEG Triboelectric nanogenerator based sensor has excellent material compatibility, low cost, and flexibility, which is a unique candidate technology for artificial intelligence. Triboelectric nanogenerators effectively provide critical infrastructure for new generation of sensing systems that collect information by large amounts of self-powered sensors. This review mainly discusses capability and prospect of triboelectric nanogenerators being applied to intelligent sports, security, touch control, and document management systems. The above fields have paid increasing attention in artificial intelligence technologies, such as machine learning, big data processing and cloud computing, demanding huge amount of sensors and complicated sensors network. Journal Article Nano Energy 84 105887 Elsevier BV 2211-2855 Triboelectric Nanogenerator, Self-powered sensor, Artificial intelligence, Machine learning, Internet of things 1 6 2021 2021-06-01 10.1016/j.nanoen.2021.105887 COLLEGE NANME Electronic and Electrical Engineering COLLEGE CODE EEEG Swansea University 2021-02-26T14:14:16.0117870 2021-02-15T10:25:41.1372120 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Yuankai Zhou 1 Maoliang Shen 2 Xin Cui 3 Yicheng Shao 4 Lijie Li 0000-0003-4630-7692 5 Yan Zhang 6 56257__19327__ef768686b64b4f10bce00fd15a60beb8.pdf 56257.pdf 2021-02-18T09:03:08.2430583 Output 2178556 application/pdf Accepted Manuscript true 2022-02-15T00:00:00.0000000 ©2021 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND) true eng http://creativecommons.org/licenses/by-nc-nd/4.0/
title Triboelectric nanogenerator based self-powered sensor for artificial intelligence
spellingShingle Triboelectric nanogenerator based self-powered sensor for artificial intelligence
Lijie Li
title_short Triboelectric nanogenerator based self-powered sensor for artificial intelligence
title_full Triboelectric nanogenerator based self-powered sensor for artificial intelligence
title_fullStr Triboelectric nanogenerator based self-powered sensor for artificial intelligence
title_full_unstemmed Triboelectric nanogenerator based self-powered sensor for artificial intelligence
title_sort Triboelectric nanogenerator based self-powered sensor for artificial intelligence
author_id_str_mv ed2c658b77679a28e4c1dcf95af06bd6
author_id_fullname_str_mv ed2c658b77679a28e4c1dcf95af06bd6_***_Lijie Li
author Lijie Li
author2 Yuankai Zhou
Maoliang Shen
Xin Cui
Yicheng Shao
Lijie Li
Yan Zhang
format Journal article
container_title Nano Energy
container_volume 84
container_start_page 105887
publishDate 2021
institution Swansea University
issn 2211-2855
doi_str_mv 10.1016/j.nanoen.2021.105887
publisher Elsevier BV
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
document_store_str 1
active_str 0
description Triboelectric nanogenerator based sensor has excellent material compatibility, low cost, and flexibility, which is a unique candidate technology for artificial intelligence. Triboelectric nanogenerators effectively provide critical infrastructure for new generation of sensing systems that collect information by large amounts of self-powered sensors. This review mainly discusses capability and prospect of triboelectric nanogenerators being applied to intelligent sports, security, touch control, and document management systems. The above fields have paid increasing attention in artificial intelligence technologies, such as machine learning, big data processing and cloud computing, demanding huge amount of sensors and complicated sensors network.
published_date 2021-06-01T04:11:04Z
_version_ 1763753763790651392
score 11.016258

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