Design and Fabrication of Ultra-Narrow Band High-Temperature Superconducting Filter with 1 MHz Bandwith

Shuai Shang, Xilong Lu, Yue Yin, Qingyu Kong, Rui Zhang

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

Abstract

This paper propose the fast deign model based on the ANN (artificial neural networks), the model can be used to accurately predict the performance of the HTS (high-temperature superconducting) filter. Four spiral-in-spiral-out (SISO) resonators are used to design an ultra-narrow band superconducting filter to demonstrate the proposed fast model. The coupling coefficient is rather weak and a pair of transmission zeros are introduced by non-adjacent couplings, the simulated filter response is well agree with the ANN predicted response. The superconducting filter passband is 2432.9 MHz - 2434.2 MHz with the ultra-narrow fractional bandwidths of 0.05%. The measured results agree well with the simulated ones, the insertion loss is less than 0.5 dB and the return loss is better than -12 dB.

Original languageEnglish
Title of host publicationProceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350358971
DOIs
StatePublished - 2023
Event2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023 - Guilin, China
Duration: 10 Nov 202313 Nov 2023

Publication series

NameProceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

Conference

Conference2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023
Country/TerritoryChina
CityGuilin
Period10/11/2313/11/23

Keywords

  • ANN (artificial neural networks)
  • high-temperature superconducting (HTS) filter
  • ultra-narrow band

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