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Record W2040209036 · doi:10.5539/mas.v4n6p8

High-performance Grating Coupled Surface Plasmon Resonance Sensor Based on Al-Au Bimetallic Layer

2010· article· en· W2040209036 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceSurface plasmon resonanceFull width at half maximumBimetallic stripGratingRefractive indexOpticsSurface plasmonDiffractionResonance (particle physics)PlasmonDiffraction gratingOptoelectronicsMetalNanoparticleNanotechnologyPhysics

Abstract

fetched live from OpenAlex

A high-performance grating coupled surface plasmon resonance (GCSPR) sensor based on Al-Au bimetallic layer is proposed. High sensitivity is obtained by replacing the positive diffraction order with negative diffraction order of metallic grating to excite the surface plasmon. Compared with the conventional Au-based GCSPR sensor, the sensor with aluminum as the SPR active metal exhibits a sharper (i.e. larger depth-to-width ratio) reflectivity dip, which increases the signal-to-noise ratio (SNR) and enhances its resolution. In addition, an ultrathin gold film is deposited on the grating surface in order to protect the Al layer from getting oxidized. Numerical simulations show that the angular sensitivity of the sensor reaches 187.2°/RIU (degree per refractive index unit) with good linearity and the FWHM (full width at half maximum) of the resonant dip is only 0.93°.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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