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Record W1963878141 · doi:10.1049/iet-map.2013.0081

Study of <i>Q</i> ‐factors of ridge and groove gap waveguide resonators

2013· article· en· W1963878141 on OpenAlexaff
Elena Pucci, Ashraf Uz Zaman, Eva Rajo‐Iglesias, Per‐Simon Kildal, Ahmed A. Kishk

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
FundersVetenskapsrådet
KeywordsRidgeResonatorGroove (engineering)OpticsMaterials scienceOptoelectronicsPhysicsEngineeringGeologyMechanical engineering

Abstract

fetched live from OpenAlex

The gap waveguide technology for millimeter waves applications has been recently presented. The new structure is made by generating a parallel plate cut‐off region between an artificial magnetic conductor (AMC) and a metallic plate. Propagating waves will be only allowed to follow a metal ridge or groove surrounded by the AMC. The gap waveguide can be made of only metal and does not need any contact between the metal joints compared to standard waveguides. In this study, a study of Q ‐factors of resonators made in ridge and groove gap waveguides are presented. The resonators are made of copper and the AMC used is a textured surface of metallic pins. Simulated and measured unloaded Q s are presented and compared with Q of a standard rectangular waveguide. High Q ‐factors are measured for the prototypes presented, approaching 90–96% of the simulated values. Furthermore, it is shown how the lid of pins can easily stop the leakage loss at the joints of the circuit, which is the typical cause of reduced Q ‐factor of standard waveguides at high frequency.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.014
GPT teacher head0.210
Teacher spread0.196 · 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 designSimulation or modeling
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

Citations99
Published2013
Admission routes1
Has abstractyes

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