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Record W2077933680 · doi:10.1049/iet-map:20070009

Efficient and accurate design of substrate-integrated waveguide circuits synthesised with metallic via-slot arrays

2008· article· en· W2077933680 on OpenAlexaff
Feng Xu, Xiaohong Jiang, Kehui Wu

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2008
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsResonatorElectronic circuitWaveguideMaterials scienceLeakage (economics)Substrate (aquarium)Integrated circuitDimension (graph theory)Equivalent circuitOptoelectronicsElectronic engineeringElectrical engineeringMathematicsEngineering

Abstract

fetched live from OpenAlex

A new class of substrate-integrated waveguides (SIWs) is proposed, which highlights a novel synthesis of waveguide circuits using metallic via-slot arrays instead of via-hole arrays. When the gaps between the slots are small enough, the broadside dimension of equivalent rectangular waveguide is approximately equal to the spacing between the inner walls of slots. Therefore the size of the SIW can directly be used to calculate propagation constants almost without phase bias. This new design is of critical importance in the design of substrate-integrated circuits (SICs) with fine and sensitive geometrical details with respect to circuit response such as filters and resonators. In this way, the design of SICs based on the new SIW structures can greatly be simplified. A finite difference frequency-domain method accelerated by an implicitly restarted Arnoldi method is developed to model the substrate-integrated resonant cavities with leakage. Simulated and measured results have confirmed the fact that conventional waveguide components are very similar to the SIW counterparts of the same structure.

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 score0.416
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 head0.018
GPT teacher head0.196
Teacher spread0.177 · 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

Citations14
Published2008
Admission routes1
Has abstractyes

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