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Record W2954116736 · doi:10.1088/1361-6528/ab2ce8

Infrared plasmonic meta-modes via near-field coupling of metallic nanorods with split-ring resonators

2019· article· en· W2954116736 on OpenAlexaff
Rithvik R. Gutha, Seyed M. Sadeghi, Christina Sharp, Ali Hatef

Bibliographic record

VenueNanotechnology · 2019
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsNipissing University
FundersUniversity of Alabama in Huntsville
KeywordsNanorodMaterials sciencePlasmonResonatorSplit-ring resonatorDipoleQuadrupoleOptoelectronicsElectric fieldMolecular physicsOpticsCondensed matter physicsNanotechnologyPhysicsAtomic physics

Abstract

fetched live from OpenAlex

We study the anomalous optical properties of lattices formed via periodic arrangement of a plasmonic unit structure consisting of a metallic nanorod and U-shape split-ring resonator. When the units are closely packed, i.e., small lattice constants, and the incident light is polarized along the transverse axis of the nanorods, our results show that the near-field plasmonic coupling of these units leads to a lattice-induced meta-mode. Such a meta-mode is not an intrinsic mode of these units or their constituents (nanorods and split-ring resonator), rather it is formed via capacitive coupling of the split-ring resonator of one unit with the nanorod of another unit. This leads to a unique charge distribution, generating a strong field accumulation at the center of the nanorod. We show that this assimilates a plasmon field profile similar to that of the intrinsic quadrupole mode of the nanorods, although it occurs at wavelengths longer than their dipole modes. Our results show that such a meta-mode generates a narrow dominant optical feature in the infrared range (∼1.5 μm) with significant immunity against the rotation of the lattices.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 spread0.215 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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