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Record W4409497222 · doi:10.1088/2515-7647/adcddd

Impact of permittivity grading on coupled resonance in hybrid-ENZ metasurfaces

2025· article· en· W4409497222 on OpenAlexaff
Anindita Das, Laura C. Wynne, Andrea Di Falco, Sebastian A. Schulz

Bibliographic record

VenueJournal of Physics Photonics · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Waterloo
FundersH2020 European Research CouncilEngineering and Physical Sciences Research Council
KeywordsPermittivityMaterials scienceGrading (engineering)Resonance (particle physics)OpticsOptoelectronicsPhysicsDielectricEngineeringAtomic physics

Abstract

fetched live from OpenAlex

Abstract Hybrid-epsilon-near-zero (ENZ) metasurfaces, consisting of nanoantenna arrays on thin films of ENZ materials, feature a coupled resonance spectrum and have gathered significant interest for their nonlinear optical properties and their use in electro-optically tunable metasurfaces. While typically assumed to have a uniform permittivity, the ENZ film often features a graded permittivity distribution as a consequence of either material growth or capacitive tuning. Here we assess the impact of such a permittivity grading on the coupled resonance spectrum and show that the presence of grading alone results in a strong shift of the transmission minima of the coupled resonance, providing a new design parameter for hybrid-ENZ metasurfaces.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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