Dielectric Property Retrieval with Open-Ended Coaxial Probe for Solid Materials

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Determining the dielectric properties of materials based on their microwave features is an important research topic in various disciplines and industries. Accurate retrieval of solid material dielectric properties is one of the challenges in non-destructive measurement approaches. In this work, the dielectric property of three different flat-surface solid materials (kestamid, delrin and alumina) were retrieved from reflection coefficients through deep learning model from 0.5 to 6 GHz. The deep learning model was designed based on Debye parameters and reflection coefficients computed from the open-ended coaxial probe admittance model. The results were compared with commercially available Speag Dielectric Assessment Kit (DAK) software and the calculated percentage dielectric property differences are 5.5%, 6.8% and 7.5% for kestamid, delrin and alumina, respectively.

Original languageEnglish
Title of host publication2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-14
Number of pages2
ISBN (Electronic)9781946815163
DOIs
Publication statusPublished - 2022
Event2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2022 - Denver, United States
Duration: 10 Jul 202215 Jul 2022

Publication series

Name2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2022 - Proceedings

Conference

Conference2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2022
Country/TerritoryUnited States
CityDenver
Period10/07/2215/07/22

Bibliographical note

Publisher Copyright:
© 2022 USNC-URSI.

Funding

ACKNOWLEDGEMENT This work has received funding from Scientific and Technological Research Council of Turkey under grant agreement 118S074 and COST Action grant agreement CA17115.

FundersFunder number
European Cooperation in Science and TechnologyCA17115
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu118S074

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