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Record W4405098299 · doi:10.1088/1361-6463/ad9b36

Surface plasmon resonance excitation and imaging in circular gratings: a study of non-polarized, radial and azimuthal polarization effects

2024· article· en· W4405098299 on OpenAlexafffund
Eoin Dawson, A. V. Novikova, Yazan Bdour, Ribal Georges Sabat

Bibliographic record

VenueJournal of Physics D Applied Physics · 2024
Typearticle
Languageen
FieldMaterials Science
TopicOptical Coatings and Gratings
Canadian institutionsRoyal Military College of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolarization (electrochemistry)AzimuthExcitationSurface plasmon resonanceResonance (particle physics)OpticsSurface plasmonRadial polarizationPlasmonPhysicsLocalized surface plasmonMaterials scienceAtomic physicsChemistryNanotechnologyLaser beamsNanoparticle

Abstract

fetched live from OpenAlex

Abstract This study explores the effects of various polarization states on surface plasmon resonance (SPR) in circular gratings, emphasizing their potential in sensing technologies. We present a mathematical modeling framework alongside experimental investigations involving the fabrication and characterization of circular gratings using linearly polarized, radially polarized, and non-polarized light. Our findings demonstrate stable SPR responses across multiple polarization angles, with strong signals achievable even with non-polarized light, minimizing reliance on polarizers. Additionally, we analyze spatial intensity responses and the influence of polarization on excitation patterns, enhancing our understanding of plasmonic interactions. Through Surface Plasmon Resonance imaging (SPRi), we highlight the capability to capture topographical information, further contributing to advancements in plasmonics and the development of improved sensing devices.

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 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 score0.272
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.243
Teacher spread0.236 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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