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Record W2076132077 · doi:10.1364/oe.21.000079

Highly tunable nanoscale metal-insulator-metal split ring core ring resonators (SRCRRs)

2013· article· en· W2076132077 on OpenAlexaff
Iman Zand, Mohammad Sadegh Abrishamian, Pierre Berini

Bibliographic record

VenueOptics Express · 2013
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsResonatorOpticsMaterials scienceFree spectral rangeSplit-ring resonatorOptoelectronicsRefractive indexNanoscopic scaleHelical resonatorCore (optical fiber)Coupled mode theoryMetal-insulator-metalResonance (particle physics)Optical ring resonatorsPhysicsNanotechnologyVoltage

Abstract

fetched live from OpenAlex

A class of nano-scale wavelength-selective optical filters is proposed where the core of a metal-insulator-metal square ring is replaced with a split-ring core (SRC). The proposed resonator supports split-ring-resonator-like (SRR-like) resonant modes that are characteristics of the structure. These resonant modes are highly adjustable, via the gap size of the split-ring core, over a range of hundreds of nanometers. The proposed resonator can also incorporate tunable materials localized in the gap of the SRC or placed throughout the resonating path. By varying the refractive index (1 to 2) of the material in the gap of the SRC, first and second SRR-like modes can be tuned over ~200 and 300 nm, respectively. A circuit model based on transmission-line theory is proposed for the structure and used to derive the resonance conditions of the split-ring-resonator-like modes; the model compares favorably to the numerical results. The proposed resonator has the potential to be utilized effectively in integrated nano-scale optical switches and tunable filters.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.215
Teacher spread0.202 · 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 teacher head, not a consensus.

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

Citations47
Published2013
Admission routes1
Has abstractyes

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