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Advanced Spoof Surface Plasmon Polaritons based Wide Angle Broadband Dual-Beam Scanning Leaky-wave Antenna for sub-6 GHz Applications

2023· article· en· W4392027291 on OpenAlexaff
Ravi Anand, Amine Mezghani, Anirban Sarkar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSurface plasmon polaritonLeaky wave antennaBroadbandOpticsPlasmonMaterials scienceOptoelectronicsSurface plasmonAntenna (radio)Surface wavePhysicsMicrostrip antennaComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

This work presents a new idea of planar single layer spoof surface plasmon polaritons transmission line (SSPP-TL) based wide angle dual-beam scanning antenna for sub-6GHz applications. A unique kind of groundless single layered (S-L) SSPP-TL is proposed using binary tree shape metallic grooves. This unique pattern on the substrate generates propagating slow-wave mode in the desired frequency range. For generation of the radiating fast-mode, hexagonal patches are arranged periodically in the close proximity of the metallic groove to achieve fast beam steering with complete elimination of open stopband (OSB) effect. The calculated and numerically simulated results show that the dual-beam steering of 326° (from ± 85° to ± 78°) is achieved in visible space while frequency sweeps from 3.92 GHz to 7.58 GHz in the sub-6 GHz band with maximum gain of 14.92 dB. The fractional bandwidth of 141.35 % is achieved for the proposed designed antenna.

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 score0.002

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.257
Teacher spread0.235 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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