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Record W2976909123 · doi:10.1021/acsphotonics.9b01179

Carving Plasmon Modes in Silver Sierpiński Fractals

2019· article· en· W2976909123 on OpenAlexafffund
Isobel C. Bicket, Edson P. Bellido, Danielle M. McRae, François Lagugné‐Labarthet, Gianluigi A. Botton

Bibliographic record

VenueACS Photonics · 2019
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsCanadian Light Source (Canada)Western UniversityMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFractalOpticsAperture (computer memory)DipolePhysicsGeometryAcousticsMathematicsMathematical analysisQuantum mechanics

Abstract

fetched live from OpenAlex

The surface plasmon resonance (SPR) modes of the first three generations of a Sierpiński fractal triangle are investigated using electron energy loss spectroscopy (EELS) complemented with finite difference time domain simulations. The Sierpiński fractal geometry is created in a subtractive manner, by carving triangular apertures into the triangular prism of the previous fractal generation. The ability of the fractal antenna to efficiently utilize space in coupling to long wavelength excitations is confirmed on the single nanostructure level via redshifting of the primary dipole mode as the fractal generation is increased. Through application of the Babinet principle, it is demonstrated that this spectral shift is caused by coupling of two degenerate orthogonal dipolar modes of a single triangle with two degenerate orthogonal dipole modes of the triangular aperture occupying the center of the first generation fractal. It is also shown that the spectral position and strength of the dipole mode can be tuned by altering the size of the central aperture, and thus the capacitance of the equivalent circuit, and the width of the conductive channels joining different fractal building blocks, thereby altering the circuit inductance. Importantly, placing the aperture on a node of the SPR mode causes a shift in energy of this mode without changing the charge configuration; placing the aperture on an antinode of the SPR mode causes no shift in energy, but changes the field configuration, as revealed through EELS measurements. These fractal-specific properties provide new strategies to design, predict, and effectively exploit highly tunable SPR modes using simple building blocks.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.948

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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 designSimulation or modeling
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

Citations10
Published2019
Admission routes2
Has abstractyes

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