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Record W2591018555 · doi:10.1021/acsphotonics.6b00979

Experimental Demonstration of Tunable Directional Scattering of Visible Light from All-Dielectric Asymmetric Dimers

2017· article· en· W2591018555 on OpenAlexafffund
Toshihiko Shibanuma, Takayuki Matsui, Tyler Roschuk, Jacek Wójcik, Peter Mascher, Pablo Albella, Stefan A. Maier

Bibliographic record

VenueACS Photonics · 2017
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsMcMaster University
FundersOffice of Naval Research GlobalUniversidad de Las Palmas de Gran CanariaU.S. ArmyAgencia Canaria de Investigación, Innovación y Sociedad de la InformaciónNatural Sciences and Engineering Research Council of CanadaEngineering and Physical Sciences Research CouncilLeverhulme Trust
KeywordsMaterials scienceScatteringDielectricOpticsLight scatteringOptoelectronicsWavelengthRefractive indexSubstrate (aquarium)PrismPhysics

Abstract

fetched live from OpenAlex

Due to the presence of strong magnetic resonances, high refractive index dielectric nanoantennnas have shown the ability to expand the methods available for controlling electromagnetic waves in the subwavelength region. In this work, we experimentally demonstrate that an asymmetric dielectric dimer made of silicon can lead to highly directional scattering depending on the excitation wavelength, due to the interference of the excited magnetic resonances. A back focal plane imaging system combined with a prism coupling technique enables us to explore the scattering profile parallel to the substrate. The directivity of scattering along the substrate is high enough to produce selective guiding of light along the substrate. These results showing tunable control of directional scattering will encourage the realization of novel optical applications, such as optical nanocircuitry.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.558

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 head0.019
GPT teacher head0.265
Teacher spread0.246 · 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

Citations88
Published2017
Admission routes2
Has abstractyes

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