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Record W2158768238 · doi:10.2528/pier13080802

DIPOLE RADIATION NEAR ANISOTROPIC LOW-PERMITTIVITY MEDIA

2013· article· en· W2158768238 on OpenAlexafffund
Mohammad Memarian, George V. Eleftheriades

Bibliographic record

VenueElectromagnetic waves · 2013
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDipolePermittivityAnisotropyRadiationMaterials scienceCondensed matter physicsComputational physicsPhysicsOpticsOptoelectronicsDielectricQuantum mechanics

Abstract

fetched live from OpenAlex

We investigate radiation of a dipole at or below the interface of (an)isotropic Epsilon Near Zero (ENZ) media, akin to the classic problem of a dipole above a dielectric half-space.To this end, the radiation patterns of dipoles at the interface of air and a general anisotropic medium (or immersed inside the medium) are derived using the Lorentz reciprocity method.By using an ENZ half-space, air takes on the role of the denser medium.Thus we obtain shaped radiation patterns in air which were only previously attainable inside the dielectric half-space.We then follow the early work of Collin on anisotropic artificial dielectrics which readily enables the implementation of practical anisotropic ENZs by simply stacking sub-wavelength periodic bi-layers of metal and dielectric at optical frequencies.We show that when such a realistic anisotropic ENZ has a low longitudinal permittivity, the desired shaped radiation patterns are achieved in air.In such cases the radiation is also much stronger in air than in the ENZ media, as air is the denser medium.Moreover, we investigate the subtle differences of the dipolar patterns when the anisotropic ENZ dispersion is either elliptic or hyperbolic.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Citations8
Published2013
Admission routes2
Has abstractyes

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