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Record W2341996662 · doi:10.1038/srep15852

Nanoscale volume confinement and fluorescence enhancement with double nanohole aperture

2015· article· en· W2341996662 on OpenAlexafffund
Raju Regmi, Ahmed Al Balushi, Hervé Rigneault, Reuven Gordon, Jérôme Wenger

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Victoria
FundersFP7 Information and Communication TechnologiesNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsFluorescence correlation spectroscopyFluorescenceNanoscopic scaleMaterials scienceNanolithographyDiffractionMoleculeOpticsConfocalResolution (logic)SpectroscopySingle-molecule experimentVolume (thermodynamics)Fluorescence spectroscopyNanotechnologyChemistryPhysicsFabrication

Abstract

fetched live from OpenAlex

Diffraction ultimately limits the fluorescence collected from a single molecule, and sets an upper limit to the maximum concentration to isolate a single molecule in the detection volume. To overcome these limitations, we introduce here the use of a double nanohole structure with 25 nm gap, and report enhanced detection of single fluorescent molecules in concentrated solutions exceeding 20 micromolar. The nanometer gap concentrates the light into an apex volume down to 70 zeptoliter (10(-21) L), 7000-fold below the diffraction-limited confocal volume. Using fluorescence correlation spectroscopy and time-correlated photon counting, we measure fluorescence enhancement up to 100-fold, together with local density of optical states (LDOS) enhancement of 30-fold. The distinctive features of double nanoholes combining high local field enhancement, efficient background screening and relative nanofabrication simplicity offer new strategies for real time investigation of biochemical events with single molecule resolution at high concentrations.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.476

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 head0.017
GPT teacher head0.226
Teacher spread0.209 · 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 designNot applicable
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

Citations60
Published2015
Admission routes2
Has abstractyes

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