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Colorimetric sensors using nano-patch surface plasmon resonators

2013· article· en· W2071613547 on OpenAlexafffund
Mohammadreza Khorasaninejad, S. Mohsen Raeis-Zadeh, Hadi Amarloo, Navid Abedzadeh, Safieddin Safavi‐Naeini, Simarjeet S. Saini

Bibliographic record

VenueNanotechnology · 2013
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Waterloo
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaResearch and Innovation FoundationIndustry Canada
KeywordsMaterials scienceRefractive indexSurface plasmon resonanceOpticsGratingWavelengthSiliconOptoelectronicsPlasmonSurface plasmonSilicon dioxideNano-ResonatorNanotechnologyNanoparticle

Abstract

fetched live from OpenAlex

A two-dimensional array of gold nano-patches on a highly reflective mirror is proposed for refractive index sensing based on changes in the reflected colors. The grating on the mirror creates localized surface plasmon resonances resulting in a minimum in the visible reflectance spectra. The wavelength of the resonance can be tuned by changing the width of the nano-patches and is also dependent on the refractive index of the surrounding medium. The color variation due to change in the refractive index is measured and used to realize a simple low-cost sensor with a refractive index resolution better than 10⁻⁵ just using image processing. The efficacy of the proposed sensor is also demonstrated for surface sensing by depositing thin layers of silicon dioxide. The color difference due to the addition of a 3 nm thick layer of silicon dioxide is detectable by the naked eye and deposition thickness of 2 Å can be resolved using image processing.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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

Citations33
Published2013
Admission routes2
Has abstractyes

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