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Record W3080442404 · doi:10.1109/tmtt.2020.3016310

Compact Mechanically Tunable Microstrip Bandstop Filter With Constant Absolute Bandwidth Using an Embedded Metamaterial-Based EBG

2020· article· en· W3080442404 on OpenAlexafffund
Jacob A. Brown, Stuart Barth, Braden P. Smyth, Ashwin K. Iyer

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutions3v Geomatics (Canada)University of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsBand-stop filterMetamaterialMaterials scienceMicrostripDielectricPlanarBandwidth (computing)PermittivityOptoelectronicsBand-pass filterOpticsLow-pass filterComputer sciencePhysicsTelecommunications

Abstract

fetched live from OpenAlex

A mechanically tunable, constant-absolute-bandwidth (ABW) bandstop filter is realized using the metamaterial-based electromagnetic bandgap structure (MTM-EBG). The MTM-EBG is embedded within a microstrip (MS) line and used to produce a bandstop filtering response, with a topology that is compact, uniplanar, and fully printable. A three-cell MTM-EBG-based MS bandstop filter is designed and experimentally verified for operation centered at 4.18 GHz with a 10-dB rejection bandwidth of 247 MHz. This filter is then made tunable by placing a dielectric plate directly on the surface of the MTM-EBGs. Moving this plate across the surface of the MTM-EBGs changes their reactive loading and, consequently, shifts their response. To ensure a constant ABW, the dielectric plate is perforated to produce an effective plate permittivity that varies for each unit cell. The tunable filter is then fabricated, with the dielectric plate applied to the MTM-EBG-based bandstop filter using a 3-D printed superstructure. A tuning range of 3.80 GHz ± 6.2% and a 10-dB bandstop ABW of 244 MHz ± 1.3% are demonstrated, showing good agreement with the simulated data. The MTM-EBG-based tunable bandstop filter has a variation in ABW comparable to 3-D filters (which typically have substantially lower variation in ABW than fully planar filters) while occupying substantially less area than alternate planar realizations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.715
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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 teacher head, not a consensus.

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

Citations24
Published2020
Admission routes2
Has abstractyes

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