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Record W2334538937 · doi:10.1103/physreva.85.053842

Effective-medium approach to planar multilayer hyperbolic metamaterials: Strengths and limitations

2012· article· en· W2334538937 on OpenAlexafffund
Omar Kidwai, Sergei V. Zhukovsky, J. E. Sipe

Bibliographic record

VenuePhysical Review A · 2012
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMetamaterialIsotropyPlanarDielectricOpticsScatteringHomogeneousAnisotropyPhysicsMaterials scienceBoundary (topology)Computational physicsOptoelectronicsMathematical analysisMathematicsComputer science

Abstract

fetched live from OpenAlex

We express the optical properties of multilayered hyperbolic metamaterials (HMMs) in terms of the Fresnel reflection coefficients at the boundary between the metamaterial and the ambient medium. Formation of a band of bulk propagating modes in HMMs located far outside the lightcone of homogeneous isotropic media is demonstrated. Exotic behavior of HMMs, such as the broadband Purcell effect and suppressed outward scattering, is reproduced. Conditions under which a metal-dielectric multilayer can be approximated by a homogeneous effective medium with extreme anisotropy (indefinite medium) are derived. It is shown that real multilayer HMMs usually have a smaller Purcell factor than the corresponding effective medium; however, the reverse scenario is shown to be possible due to an intermediary role of short-range surface plasmon excitations in the outermost metal layer in a metal-dielectric multilayer.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.046
GPT teacher head0.339
Teacher spread0.293 · 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

Citations260
Published2012
Admission routes2
Has abstractyes

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