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Record W4407831720 · doi:10.1109/tmtt.2025.3542357

PCM-Based Bandwidth-Reconfigurable Acoustic-Wave Filter

2025· article· en· W4407831720 on OpenAlexaff
Matthew Ou, Raafat R. Mansour

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Adaptive Filtering Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBandwidth (computing)AcousticsElectronic engineeringComputer sciencePhysicsEngineeringElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

We present the design, fabrication, and experimental testing of bandwidth-reconfigurable surface acoustic-wave (SAW) filters with integrated vanadium dioxide (VO2)-based radio frequency (RF) switches. We propose a design that utilizes the phase-change properties of VO2, which transitions between insulating and conductive states to enable dynamic reconfiguration of the SAW filter bandwidth. By modifying the interdigital transducer (IDT) configurations, the electromechanical coupling coefficient (k2) of the resonators can be varied, thus enabling the reconfiguration across different bandwidths. Experimental results demonstrated the bandwidth adjustability offered by the proposed design, and the fabricated prototype filters suggested that monolithically integrated VO2-based RF switches can provide a flexible solution for reconfigurable acoustic filters. To the best of our knowledge, this work represents the first demonstration of bandwidth-reconfigurable acoustic filters with monolithically integrated RF switches with acoustic resonators.

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 score0.003

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 head0.228
Teacher spread0.217 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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