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Record W2108028690 · doi:10.1109/jstqe.2008.917534

Characteristic Impedance Model for Plasmonic Metal Slot Waveguides

2008· article· en· W2108028690 on OpenAlexfundno aff
Dany-Sebastien Ly-Gagnon, Şükrü Ekin Kocabaş, David A. B. Miller

Bibliographic record

VenueIEEE Journal of Selected Topics in Quantum Electronics · 2008
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsnot available
FundersPolytechnique Montréal
KeywordsFinite-difference time-domain methodPlasmonElectrical impedanceWaveguidePhotodetectorDetectorOpticsTransmission (telecommunications)OptoelectronicsMaterials sciencePhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

We investigate the transmission properties of a subwavelength plasmonic slot waveguide. We show that the transmission can be accurately calculated using the characteristic impedance of the propagating mode. Using such a model, we show that it is possible to design devices without extensive 3-D finite-difference time-domain (FDTD) computer simulations. We illustrate the approach with calculations of an asymmetric Fabry-Perot germanium photodetector based on the slot waveguide geometry, showing predicted detector efficiencies as high as 69% despite metallic losses.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.031
GPT teacher head0.263
Teacher spread0.232 · 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 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

Citations35
Published2008
Admission routes1
Has abstractyes

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