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Record W4396686605 · doi:10.1063/5.0195583

Polarization-controlled unidirectional lattice plasmon modes via a multipolar plasmonic metasurface

2024· article· en· W4396686605 on OpenAlexafffund
S. Hamed Shams Mousavi, Muhammad Abdullah Butt, Zeinab Jafari, Orad Reshef, Robert W. Boyd, Peter Banzer, Israel De Leon

Bibliographic record

VenueApplied Physics Letters · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Ottawa
FundersArmy Research OfficeOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaDefense Advanced Research Projects AgencyCanada Research ChairsU.S. Department of EnergyNational Science Foundation
KeywordsPlasmonPolarization (electrochemistry)OptoelectronicsOpticsGratingPhysicsMetamaterialSurface plasmonNanophotonicsDiffractionMaterials scienceChemistry

Abstract

fetched live from OpenAlex

Diffractive plasmonic metasurfaces offer the possibility of controlling the flow of light in flat optical systems through the excitation of lattice plasmon modes by a careful metasurface design. Nonetheless, a remaining challenge for this type of structure is the dynamic control of its optical properties via degrees of freedom, such as the polarization states of incoming light. In this report, we explain theoretically and demonstrate experimentally the polarization control over amplitude and propagation direction of lattice plasmon modes supported by a multipolar plasmonic metasurface. These unidirectional optical waves result from the coupling between near-field effects of individual meta-atoms and far-field effects originating from the lattice modes. The device operates over a broad wavelength range, maintaining its directional behavior and enabling it to operate also as a polarization-controlled directional diffraction grating, a power splitter, or an optical router for on-chip photonics applications.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.002

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 head0.015
GPT teacher head0.237
Teacher spread0.223 · 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 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

Citations4
Published2024
Admission routes2
Has abstractyes

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