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Record W4312715962 · doi:10.1109/tmtt.2022.3222303

Reconfigurable SAW Resonators and Tunable Filters Using Monolithically Integrated VO₂ Switches

2022· article· en· W4312715962 on OpenAlexafffund
Arash Fouladi Azarnaminy, Raafat R. Mansour

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2022
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsResonatorCenter frequencyMaterials scienceOptoelectronicsCoupling coefficient of resonatorsInsertion lossQ factorElectronic engineeringBandwidth (computing)Filter (signal processing)Band-pass filterElectrical engineeringComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This article presents novel reconfigurable surface acoustic wave (SAW) resonators using switching elements based on vanadium oxide (VO2) phase change material. The switching elements are integrated monolithically with the resonators on the same chip using an in-house fabrication process, which allows the compact implementation of the proposed reconfigurable resonators. The frequency of the resonator is tuned between two different states by changing the configuration of interdigitated electrodes within the SAW resonator and by using a set of tuning electrodes and VO2 switches. Experimental results are presented for the first reconfigurable resonator with six VO2 switching elements. The resonator is tuned from 700 to 720 MHz, while the quality factor is maintained above 350 over the tuning range. A second reconfigurable resonator with a modified structure is proposed to reduce the number of required VO2 switching elements for an even more compact implementation and reduction in the required dc power consumption. The second reconfigurable resonator based on a single VO2 switching element has a tuning range from 712 to 730 MHz and a quality factor better than 514. Design, implementation, and measurement results for tunable filters based on the proposed frequency tuning method are presented. A proof-of-concept six-pole tunable filter shows center frequency tuning from 944 to 971 MHz with a 36-MHz bandwidth and an insertion loss better than 3.6 dB over the tuning range. Another three-pole filter is implemented using the proposed reconfigurable resonators with monolithically integrated VO2 switches. The filter demonstrates a measured center frequency of 713 and 733 MHz for the low and high channels, respectively, while the insertion loss is better than 2.5 dB. High power and nonlinear test results are presented for both the reconfigurable resonators and filters. The monolithic integration of the VO2 switches with SAW resonators allows the practical implementation of higher order tunable SAW filters for wireless applications without any major performance degradation or increase in the size of the filter.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.214
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2022
Admission routes2
Has abstractyes

Explore more

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