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Record W3132054114 · doi:10.1088/2632-959x/abe991

Surface-enhanced Raman scattering effect in binary systems formed by graphene on aluminum plasmonic nanostructures

2021· article· en· W3132054114 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.

fundA Canadian funder is recorded on the work.
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

VenueNano Express · 2021
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsnot available
FundersUniversidad Nacional Autónoma de MéxicoCanadian Institute for Theoretical Astrophysics
KeywordsRhodamine 6GRaman scatteringMaterials scienceGrapheneAnodizingRaman spectroscopyPlasmonNanostructureMoleculeAluminiumFluorescenceNanotechnologyOptoelectronicsPhotochemistryChemistryOpticsComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Binary systems (BS) formed by graphene (GR) deposited on top of aluminum (Al) nanoconcaves (Al-NC) and Al nanodomes (Al-ND) were synthesized by electrochemical anodization of Al. Using the plasmonic response of Al-NC and Al-ND and the distinctive physical and chemical properties of GR, these BS are proposed as Surface-Enhanced Raman Scattering (SERS) sensors using rhodamine 6G (R6G) as a proof molecule. As expected, the BS significantly enhances Raman signals of R6G molecules in comparison with substrates used as references, also suppressing the fluorescence background of R6G molecules.

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)0.000
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 score0.001
Threshold uncertainty score0.696

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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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