Artificial intelligence enhanced mathematical modeling on rotary triboelectric nanogenerators under various kinematic and geometric conditions

Khorsand, M; Tavakoli, J; Guan, H; Tang, Y

Artificial intelligence enhanced mathematical modeling on rotary triboelectric nanogenerators under various kinematic and geometric conditions

Khorsand, M Tavakoli, J

Guan, H Tang, Y

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Nano Energy, 2020, 75, pp. 1-12
Issue Date:: 2020-09-01

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Field	Value	Language
dc.contributor.author	Khorsand, M
dc.contributor.author	Tavakoli, J https://orcid.org/0000-0002-0696-6530
dc.contributor.author	Guan, H
dc.contributor.author	Tang, Y
dc.date.accessioned	2020-10-31T22:11:06Z
dc.date.available	2020-10-31T22:11:06Z
dc.date.issued	2020-09-01
dc.identifier.citation	Nano Energy, 2020, 75, pp. 1-12
dc.identifier.issn	2211-2855
dc.identifier.uri	http://hdl.handle.net/10453/143659
dc.description.abstract	© 2020 Elsevier Ltd The triboelectric nanogenerator (TENG) has been introduced as a revolutionary technology in the renewable electrical energy generation at micro/nanoscale. In the current study, experimental and theoretical models for augmented rotary TENGs are presented. The power generated by TENGs is found to be a function of the number of segments, rotational speed, and tribo-surface spacing. Mathematical modeling combined with artificial intelligence is applied to characterize the TENG output under various kinematics and geometric conditions. Sensitivity analysis reveals that the generated energy and the matched resistance depend highly on segmentation and angular velocity rate. It is shown that the optimized harvested energy reaches 0.369 mJ at each cycle. The TENG dynamic outputs for various structural parameters are found and described. This study enhances understanding of rotation-induced periodic TENGs and reveals optimized characteristics for disk-shaped TENG energy harvesters.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Nano Energy
dc.relation.isbasedon	10.1016/j.nanoen.2020.104993
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0303 Macromolecular and Materials Chemistry, 0912 Materials Engineering, 1007 Nanotechnology
dc.title	Artificial intelligence enhanced mathematical modeling on rotary triboelectric nanogenerators under various kinematic and geometric conditions
dc.type	Journal Article
utslib.citation.volume	75
utslib.for	0303 Macromolecular and Materials Chemistry
utslib.for	0912 Materials Engineering
utslib.for	1007 Nanotechnology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2020-10-31T22:10:46Z
pubs.publication-status	Published
pubs.volume	75

Abstract:

© 2020 Elsevier Ltd The triboelectric nanogenerator (TENG) has been introduced as a revolutionary technology in the renewable electrical energy generation at micro/nanoscale. In the current study, experimental and theoretical models for augmented rotary TENGs are presented. The power generated by TENGs is found to be a function of the number of segments, rotational speed, and tribo-surface spacing. Mathematical modeling combined with artificial intelligence is applied to characterize the TENG output under various kinematics and geometric conditions. Sensitivity analysis reveals that the generated energy and the matched resistance depend highly on segmentation and angular velocity rate. It is shown that the optimized harvested energy reaches 0.369 mJ at each cycle. The TENG dynamic outputs for various structural parameters are found and described. This study enhances understanding of rotation-induced periodic TENGs and reveals optimized characteristics for disk-shaped TENG energy harvesters.

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http://hdl.handle.net/10453/143659