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Record W4401727997 · doi:10.1088/1361-6528/ad713e

Infrared routing and switching with tunable spectral bandwidth using arrays of metallic nanoantennas

2024· article· en· W4401727997 on OpenAlexaff
Seyed M. Sadeghi, H.D. Knox, Dustin T. Roberts, Rithvik R. Gutha, Christina Sharp, Ali Hatef

Bibliographic record

VenueNanotechnology · 2024
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsNipissing University
FundersDivision of Electrical, Communications and Cyber Systems
KeywordsMaterials scienceScatteringPolarization (electrochemistry)WavelengthOpticsRayOptoelectronicsBandwidth (computing)Light scatteringInfraredPhysicsTelecommunications

Abstract

fetched live from OpenAlex

Abstract We study infrared routing and switching with tunable spectral bandwidth using in-plane scattering of light by flat Au nanoantenna arrays. The base dimensions of these nanoantennas are approximately 250 by 850 nm, while their heights vary from 20 to 150 nm. Our results show that, with the increase in height, the arrays become more efficient scatterers while their spectra broaden within the 1–1.6 µ m range. Our findings demonstrate that such processes strongly depend on the incident light polarization. For a given polarization, the incident light is efficiently scattered in only two opposite directions along the plane of the arrays, with insignificant transmission. Switching such a polarization by 90 ∘ , however, suppresses this process, allowing the light to mostly pass through the arrays with minimal scattering. These unique characteristics suggest a tunable beam splitter application in the 1–1.6 µ m range and even longer wavelengths.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.570

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

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