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Record W4405520483 · doi:10.1109/ojap.2024.3506921

AMC-Based Miniaturized Waveguide With Reconfigurable Pass-Bands Below Cut-Off Frequency and Quasi-TEM Mode

2024· article· en· W4405520483 on OpenAlexaff
Vikrant Singh, Maryam Khodadadi, Mohsen Khalily, Rahim Tafazolli, Ahmed A. Kishk

Bibliographic record

VenueIEEE Open Journal of Antennas and Propagation · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceWaveguideOptoelectronicsMode (computer interface)OpticsComputer sciencePhysics

Abstract

fetched live from OpenAlex

This work introduces an innovative miniaturized transverse electromagnetic (TEM) waveguide design, which is 60% smaller than conventional metal waveguides. The proposed waveguide offers two distinct electronically reconfigurable passbands well below the cutoff frequency. This has been achieved by using sidewalls composed of reconfigurable artificial magnetic conductors (AMC), optimized to operate at 3.51 GHz and 4.37 GHz. By replacing the metal sidewalls with an AMC structure, a TEM mode can be sustained within the confined space enclosed by the waveguide structure, which otherwise would not exist in a conventional metal waveguide. This eliminates typical cut-off frequency constraints that limit the size of conventional waveguides, thereby enabling a significant miniaturization of the waveguide design. The work also proposes a reconfigurable AMC design whose operating frequency can be dynamically adjusted by applying or removing a direct current (DC) bias across the integrated PIN diodes. Additionally, this work utilizes 3D printing technology to fabricate a functional waveguide, highlighting the design’s compactness, cost-effectiveness, versatility, and fast prototyping capabilities for a wide range of microwave applications. This study therefore demonstrates the potential of using reconfigurable AMCs for compact and versatile waveguide designs that can be 3D-printed for various practical use cases and modern microwave 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.579

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 communication0.0000.001
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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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.

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
Published2024
Admission routes1
Has abstractyes

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