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Record W2554275517 · doi:10.1021/acsphotonics.6b00607

Electrochemical Control of Light Transmission through Nanohole Electrode Arrays

2016· article· en· W2554275517 on OpenAlexafffund
Mahdieh Atighilorestani, Diego P. dos Santos, Ruth Flavia Vera Villamil Jaimes, Md. Mahbubor Rahman, Márcia L. A. Temperini, Alexandre G. Brolo

Bibliographic record

VenueACS Photonics · 2016
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceElectrodeSurface plasmon resonanceConductive polymerElectrochromismOptoelectronicsNanotechnologyPolypyrrolePolymerCyclic voltammetryFabricationPlasmonElectrochemistryDopingThin filmSurface plasmonNanoparticleComposite material

Abstract

fetched live from OpenAlex

Control of the surface plasmon resonance (SPR) enhanced light transmission through array of nanoholes on gold films was achieved by modifying the metal surface with a thin layer of electroconductive polymer film. The electrochromic properties of the polymer were then triggered by tuning the electrochemical potential. Conducting polymer-modified nanohole array electrodes were prepared by electrodeposition of polypyrrole (PPy) using cyclic voltammetry. Only the gold surfaces inside the holes were accessible for film formation. The doping level of the PPy film was tuned by the electrochemical potential allowing fine control for the amount of light transmitted through the arrays. The concept demonstrated here paves the way for the fabrication of a new type of controllable nanometric optoelectronic devices based on polymeric materials.

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 score0.129
Threshold uncertainty score0.503

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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

Citations17
Published2016
Admission routes2
Has abstractyes

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