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Record W3124267066 · doi:10.1364/oe.415870

Closed-form approximation of symmetric thin-film multi-layer plasmonic dispersion equation solutions

2021· article· en· W3124267066 on OpenAlexaff
Yousef Alattar, G. Kember, Michael Čada

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCladding (metalworking)PlasmonOpticsDielectricDispersion relationMaterials scienceAttenuationThin filmInsulator (electricity)Surface plasmonWavelengthAttenuation coefficientPhysicsCondensed matter physicsOptoelectronicsNanotechnologyComposite material

Abstract

fetched live from OpenAlex

An original asymptotic method is developed and used to find closed-form approximations to the symmetric thin-film three- and multi-layer plasmonic dispersion equations. Closed-form analysis of three-layer metal-insulator-metal (MIM: "M" is metal and "I" is insulator) and IMI devices shows a complementary physics underpinning their properties. Analysis of multi-layer symmetric devices, considered for a seven-layer MIMIMIM example, uncovers a remarkable departure from the physics governing MIM and IMI features. Multi-layer propagation length and attenuation are determined by proximity, in the space of cladding thickness and wavelength, to singularities that exist in the limit of vanishing imaginary part of the cladding dielectric constant. Exploitation of this phenomenon will expand the development of a broader range of thin-film applications in optoelectronics.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.050
GPT teacher head0.264
Teacher spread0.214 · 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 designTheoretical or conceptual
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

Citations0
Published2021
Admission routes1
Has abstractyes

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