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Record W2946151886 · doi:10.1049/el.2019.1494

Low‐loss and broadband coaxial line to air‐filled substrate integrated waveguide transition

2019· article· en· W2946151886 on OpenAlexaff
Ali‐Reza Moznebi, Arash Arsanjani, Kambiz Afrooz, Pedram Mousavi

Bibliographic record

VenueElectronics Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInsertion lossMaterials scienceReturn lossCoaxialConductorOpticsBroadbandMicrostripImpedance matchingBandwidth (computing)OptoelectronicsMicrowaveWaveguideSubstrate (aquarium)Electrical impedanceElectrical engineeringTelecommunicationsPhysicsComposite materialEngineeringAntenna (radio)

Abstract

fetched live from OpenAlex

This Letter introduces a low‐loss and broadband coaxial line to air‐filled substrate integrated waveguide (AFSIW) transition for the first time. The fabrication of this transition involves three substrate layers. The inner conductor of the coaxial line is connected to the metal layer of the lower substrate and its outer conductor is connected to the metal layer of the upper substrate. This transition uses a taper‐shaped configuration at the end of the line to achieve the better impedance matching and wider matching bandwidth. In the previously reported AFSIW components, several transitions are used to transform the transverse electromagnetic mode of the coaxial line to the TE mode of the AFSIW structure. By using the proposed transition, these extra transitions are eliminated, which leads to the size and loss reduction of the structure. For validation purposes, a prototype of the back‐to‐back coaxial line to AFSIW transition is fabricated and measured for the entire C‐band. The simulated and measured results are in good agreement. The proposed transition achieves the measured insertion loss of 0.55 0.5 dB (0.28 0.25 dB for the transition) and return loss of better than from 4 to 8 GHz.

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: Empirical
Teacher disagreement score0.055
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 head0.003
GPT teacher head0.178
Teacher spread0.175 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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