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Dual-Band Unit Cell of EBG Structure for Printed Gap Waveguide

2023· article· en· W4386494892 on OpenAlexaff
Mehek. M. R. Mou, Ahmed A. Kishk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceConductorSubstrate (aquarium)OptoelectronicsRidgeMulti-band deviceDielectricPhotonic crystalOpticsElectrical engineeringAntenna (radio)Composite materialPhysicsEngineeringGeology

Abstract

fetched live from OpenAlex

A dual electromagnetic gap (EBG) is realized by a unit cell of three substrates sandwiched between two metal plates. The unit cell consists of two stacked dielectric substrates topped by an aired substrate below the top metallic plate. The unit cell consists of a large mushroom patch on the bottom grounded substrate etched on its top and connected to the lower metal plane by a conducting via. The intermediate substrate has four smaller mushroom patches of total size smaller or equal to the bottom patch, and each is connected to the lower patch by conducting vias. The total size of the one-unit cell is 1.8mm. The unit cell is designed to achieve two stop band gaps; one is for the lower band for 13–24 GHz and another for the upper band 34–44 GHz. Inserting a so-called printed ridge perturbing the periodicity creates propagating modes within the EBG bands, guiding the electromagnetic waves between the upper conductor and the ridge and suppressing them elsewhere. The simulated results are presented. They could have the potential to be used for various dual-band applications.

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 score0.005

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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
Published2023
Admission routes1
Has abstractyes

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