Simulation of high-output and lightweight sliding-mode triboelectric nanogenerators

Khorsand, M; Tavakoli, J; Kamanya, K; Tang, Y

Simulation of high-output and lightweight sliding-mode triboelectric nanogenerators

Khorsand, M Tavakoli, J

Kamanya, K Tang, Y

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Nano Energy, 2019, 66
Issue Date:: 2019-12-01

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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	Kamanya, K
dc.contributor.author	Tang, Y
dc.date.accessioned	2022-07-20T06:49:04Z
dc.date.available	2022-07-20T06:49:04Z
dc.date.issued	2019-12-01
dc.identifier.citation	Nano Energy, 2019, 66
dc.identifier.issn	2211-2855
dc.identifier.issn	2211-3282
dc.identifier.uri	http://hdl.handle.net/10453/159066
dc.description.abstract	In light of the rapid growth in microelectronic technology, triboelectric nanogenerators (TENGs) have been exploited as securely sustainable substitutes for energy scavenging purposes as well as self-powered sensory utilization. In essence, TENGs’ energy output and average power distribution depend highly on certain key parameters including contact area, the thickness of electric films and external resistance. This study attempts to predict the behavior of TENGs based on variation of those key parameters and tries to optimize the associated characteristics leading to high-output and light-weight sliding-mode TENGs. To meet this problem, an artificial intelligence approach is taken into consideration and solutions for load resistance and geometry are presented. Furthermore, an experimental setup is designed to evaluate the accuracy of the simulation results, demonstrating the precision of the applied theory. The results revealed that the predefined sliding-mode TENG can harvest 0.25 mJ at each cycle in an open-circuit condition where the weight is almost 42.91 g. Moreover, simulation proves that an appropriate value for the external resistor can increase the scavenged energy up to 3.65 mJ at each reciprocal movement. Finally, temporal responses for charge, current, voltage, power output, and harvested energy are plotted and discussed, facilitating understanding of the relationship between scavenged energy and optimized parameters.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Nano Energy
dc.relation.isbasedon	10.1016/j.nanoen.2019.104115
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0303 Macromolecular and Materials Chemistry, 0912 Materials Engineering, 1007 Nanotechnology
dc.title	Simulation of high-output and lightweight sliding-mode triboelectric nanogenerators
dc.type	Journal Article
utslib.citation.volume	66
utslib.for	0303 Macromolecular and Materials Chemistry
utslib.for	0912 Materials Engineering
utslib.for	1007 Nanotechnology
pubs.organisational-group	/University of Technology Sydney
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/Centre for Health Technologies (CHT)
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-20T06:48:51Z
pubs.publication-status	Published
pubs.volume	66

Abstract:

In light of the rapid growth in microelectronic technology, triboelectric nanogenerators (TENGs) have been exploited as securely sustainable substitutes for energy scavenging purposes as well as self-powered sensory utilization. In essence, TENGs’ energy output and average power distribution depend highly on certain key parameters including contact area, the thickness of electric films and external resistance. This study attempts to predict the behavior of TENGs based on variation of those key parameters and tries to optimize the associated characteristics leading to high-output and light-weight sliding-mode TENGs. To meet this problem, an artificial intelligence approach is taken into consideration and solutions for load resistance and geometry are presented. Furthermore, an experimental setup is designed to evaluate the accuracy of the simulation results, demonstrating the precision of the applied theory. The results revealed that the predefined sliding-mode TENG can harvest 0.25 mJ at each cycle in an open-circuit condition where the weight is almost 42.91 g. Moreover, simulation proves that an appropriate value for the external resistor can increase the scavenged energy up to 3.65 mJ at each reciprocal movement. Finally, temporal responses for charge, current, voltage, power output, and harvested energy are plotted and discussed, facilitating understanding of the relationship between scavenged energy and optimized parameters.

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http://hdl.handle.net/10453/159066