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Record W2160591851 · doi:10.1109/mwsym.2012.6259650

Simultaneous electric and magnetic two-dimensional tuning of substrate integrated waveguide cavity resonator

2012· article· en· W2160591851 on OpenAlexaff
Sulav Adhikari, Anthony Ghiotto, Ke Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsResonatorVaricapMaterials scienceCapacitorOptoelectronicsCapacitanceDiodeQ factorMagnetic fieldElectric fieldMicrowaveWaveguideFerrite (magnet)Nuclear magnetic resonanceElectrical engineeringPhysicsVoltageEngineering

Abstract

fetched live from OpenAlex

A concept of simultaneous electric and magnetic two-dimensional (2-D) tuning of cavity resonator based on substrate integrated waveguide (SIW) technology is presented and demonstrated. For a dominant TE101mode SIW cavity resonator, magnetic tuning is achieved by loading a YIG ferrite slab and electric tuning is achieved by placing a varactor diode and capacitors in the cavity. Considering only electric tuning using varactor diodes 1.3% of total tuning range is measured, while for simultaneous electric and magnetic tuning it is 7.9% with unloaded Q-factor better than 130. Using 0.05–0.1 pF of surface mount capacitor a total tuning range of 20% is experimentally achieved. Transmission line theory is used to derive a theoretical 2-D tuned resonant frequency curve, which depicts the variation of cavity resonant frequency with external applied magnetic fields and the capacitance values. The designed dual E- and H-field tunable cavity resonator is cost effective and can be applied in frequency-agile microwave systems.

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 science0.0010.001
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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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