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Record W1924457398 · doi:10.1109/jlt.2015.2477367

Highly Directive Hybrid Plasmonic Leaky-Wave Optical Antenna With Controlled Side-Lobe Level

2015· article· en· W1924457398 on OpenAlexfundno aff
Mohammad Panahi, Leila Yousefi, Mahmoud Shahabadi

Bibliographic record

VenueJournal of Lightwave Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsnot available
FundersUniversity of WaterlooIran National Science FoundationNational Science Foundation
KeywordsSide lobeDirectivityOpticsBandwidth (computing)TaperingOptoelectronicsMaterials scienceBeam steeringPlasmonReconfigurable antennaRadiation patternAntenna (radio)PhysicsTelecommunicationsComputer scienceAntenna efficiencyBeam (structure)

Abstract

fetched live from OpenAlex

Various configurations are proposed to engineer the pattern of optical leaky-wave antennas with the goal of achieving a desired side-lobe level (SLL). By the aid of the proposed algorithm, two types of hybrid plasmonic optical traveling wave antennas with controlled SLL are designed and numerically analyzed. The antennas are designed to operate at the standard telecommunication wavelength of 1550 nm, and have a wide bandwidth that completely cover the standard optical communication bands of E, S, and C. The first configuration in which the tapering is applied to the width of slots results in a broad bandwidth of 28 THz, a high directivity of 14.6 dBi, an efficiency of 73%, and a low SLL of -19.4 dB. The second configuration, in which wall tapering is applied, exhibits a bandwidth greater than 30 THz, a high directivity of 13.6 dBi, an efficiency of 79%, and an excellent SLL of -25 dB. Thanks to the high gain and low SLL, these devices can have applications in integrated optical interconnects, highly integrated optical beam-steering devices, such as active LIDARs and solar cells with high efficiency.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.032
GPT teacher head0.243
Teacher spread0.211 · 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

Citations32
Published2015
Admission routes1
Has abstractyes

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