Oyeka, Dumtoochukwu Obiora, Batchelor, John C., Saunders, Rachel (2023) A comparison of conductive ink usage optimization techniques used in fabrication of epidermal UHF radio frequency identification tags for medical and sensing applications. IET Healthcare Technology Letters, 10 (5). pp. 99-103. ISSN 2053-3713. (doi:10.1049/htl2.12051) (KAR id:103100)
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Official URL: https://doi.org/10.1049/htl2.12051 |
Abstract
The aim of this work is to assess the performance of various inkjet printing techniques. These techniques are aimed at optimizing the volume of conductive ink used in the fabrication of inkjet printed Radio Frequency Identification tags. It is also possible that they can be used in fabricating other electronic and electromagnetic devices and structures. Three ink optimization approaches were examined viz. gridded (meshed) designs, conductive area trimming and selective ink deposition. The volume of conductive ink utilized in tag fabrication and the measured on-body (forearm) read range of the tag were used to develop a figure of merit which determined the best printing approach. Although the longest read range was obtained from the tag with 48% conductive area trimming (Trim 1), the best figure of merit, that is, the tag with the best balance between measured read range and utilized conductive ink, was obtained from the tag that had its surface area trimmed by 65% (Trim 2). It is however suggested that optimum use of conductive ink would be achieved with a combination of 65% surface area trimming and selective ink deposition technique.
Item Type: | Article |
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DOI/Identification number: | 10.1049/htl2.12051 |
Additional information: | For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising. |
Uncontrolled keywords: | RFID, printed electronics, sensing |
Subjects: | T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7871.6 Antennas and waveguides |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Funders: | Engineering and Physical Sciences Research Council (https://ror.org/0439y7842) |
Depositing User: | John Batchelor |
Date Deposited: | 03 Oct 2023 14:03 UTC |
Last Modified: | 08 Feb 2024 14:52 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/103100 (The current URI for this page, for reference purposes) |
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