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Record W1973017611 · doi:10.1364/oe.18.021669

High-throughput diffraction-assisted surface-plasmon-polariton coupling by a super-wavelength slit

2010· article· en· W1973017611 on OpenAlexafffund
M. W. Maqsood, R. Mehfuz, Kenneth J. Chau

Bibliographic record

VenueOptics Express · 2010
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsCoupling (piping)Surface plasmon polaritonWavelengthSlitMaterials sciencePlasmonWaveguideSurface plasmonDielectricThroughputRefractive indexOptoelectronicsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

We propose a novel SPP coupling scheme capable of high SPP throughput and high SPP coupling efficiency based on a slit of width greater than the wavelength, immersed in a uniform dielectric. The dispersive properties of the slit are engineered such that the slit sustains a low-loss higher-order waveguide mode just above cutoff, which is shown to be amenable to wavevector matching to the SPP mode at the slit exit. The SPP throughput and SPP coupling efficiency are quantified by numerical simulations of visible light propagation through the slit for varying width and dielectric refractive index. An optimal SPP coupling configuration satisfying wavevector matching is shown to yield an order-of-magnitude greater SPP throughput than a comparable slit of sub-wavelength width and a peak SPP coupling efficiency ≃ 68%. To our knowledge, this is the first investigation of coupling between higher-order waveguide modes in slits of super-wavelength width and SPP modes.

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 score0.000
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)0.0000.000

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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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

Citations15
Published2010
Admission routes2
Has abstractyes

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