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Record W4391942706 · doi:10.1109/ojap.2024.3367664

Analysis and Design of Planar Surface Wave Lenses and Application to Leaky-Wave Antennas

2024· article· en· W4391942706 on OpenAlexaff
Maksim Kuznetcov, Davide Comite, Symon K. Podilchak, Alois P. Freundorfer, Yahia M. M. Antar

Bibliographic record

VenueIEEE Open Journal of Antennas and Propagation · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsRoyal Military College of CanadaQueen's UniversityRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsPlanarLens (geology)MicrowaveMicrostripPolarization (electrochemistry)Ground planeCommunications satelliteRadar

Abstract

fetched live from OpenAlex

Planar metasurface lens structures based on microstrip technology, optimized to control the propagation of surface waves (SWs), are presented. Two different lenses are studied, i.e., a converging or plane-wave-like lens and a diverging lens. Near-field simulations and measurements are reported to demonstrate the guiding features of the designed lenses, which have also been proposed as a feeding system for planar leaky-wave antennas (LWAs). Far-field results show improvements in terms of reduced cross polarization and sidelobe level as well as increased realized gain when compared without these SW lenses. The proposed structures are also simple to manufacture and are employed herein to control SW fields generated by a TM0 surface-wave launcher (SWL) integrated in the ground plane of the developed prototype demonstrators. Some applications include high-gain radar and remote sensing satellite antennas as well as microwave and millimeter-wave communication systems.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.051
GPT teacher head0.294
Teacher spread0.243 · 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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