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Record W2148876022 · doi:10.1364/oe.16.009708

Surface plasmon microcavity for resonant transmission through a slit in a gold film

2008· article· en· W2148876022 on OpenAlexafffund
Reuven Gordon

Bibliographic record

VenueOptics Express · 2008
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Victoria
FundersSimon Fraser University
KeywordsOpticsMaterials scienceSurface plasmonSlitSurface plasmon resonanceRaman scatteringExtraordinary optical transmissionPlasmonWavelengthResonance (particle physics)Surface plasmon polaritonOptical microcavityScatteringOptoelectronicsTransmission (telecommunications)Finite-difference time-domain methodRaman spectroscopyPhysicsLaserNanotechnologyNanoparticleAtomic physics

Abstract

fetched live from OpenAlex

We demonstrate the use of a compact surface plasmon (SP) microcavity formed in a 300 nm thick gold film to resonantly enhance the optical transmission through a subwavelength slit. Focussed ion beam milling is used to create 200 nm deep SP microcavities, with widths between 800 nm to 1300 nm, each with a 180 nm slit in its center. The experimentally-measured TM polarized optical transmission has a wavelength-dependent peak that has similarities with finite-difference time-domain calculations in terms of peak-position and enhancement factors of peak transmission. The calculations show, by observing the near-field distributions, the interaction between the SP microcavity standing waves and the slit to create enhanced transmission. The SP microcavity demonstrated here is easily fabricated and may be optimized for future applications in surface-enhanced Raman scattering, nonlinear optics and surface plasmon resonance sensors.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.925

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 communication0.0000.000
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 head0.032
GPT teacher head0.260
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations39
Published2008
Admission routes2
Has abstractyes

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