MétaCan
Menu
Back to cohort
Record W2152016613 · doi:10.1039/c4cp05252h

Tip-enhanced Raman spectroscopy of graphene-like and graphitic platelets on ultraflat gold nanoplates

2015· article· en· W2152016613 on OpenAlexafffund
Farshid Pashaee, Faranak Sharifi, Giovanni Fanchini, François Lagugné‐Labarthet

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2015
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsGrapheneRaman spectroscopyExcitationMaterials scienceSpectroscopyX-ray photoelectron spectroscopyNanotechnologyOpticsNuclear magnetic resonancePhysics

Abstract

fetched live from OpenAlex

In this study, tip-enhanced Raman spectroscopy (TERS) is used to characterize graphene-like and graphitic platelets composed of a few layers of graphene. Specifically, gap-mode TERS geometry provides a larger enhancement of the local electromagnetic field at the junction formed by a gold sharp tip and a gold substrate. Graphene-like platelets are deposited onto ultra-flat thin gold nanoplates using a surfactant-assisted method. Au-coated atomic force microscopy (AFM) tips are used to probe specific substrate regions coated by the platelets. TERS spectra are collected on distinctive points on the graphene-like layers and surrounding substrate using radially or linearly polarized light, with an excitation wavelength of 632.8 nm. The position, width and intensity of G, D, and 2D Raman-active modes of graphene are discussed as a function of the incident light polarization and for distinct positions on the graphene layer. We report here on the nature of the collected TERS spectra focusing in particular on the edges of the graphene platelets.

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 score0.017
Threshold uncertainty score0.848

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 head0.015
GPT teacher head0.238
Teacher spread0.222 · 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

Citations42
Published2015
Admission routes2
Has abstractyes

Explore more

Same venuePhysical Chemistry Chemical PhysicsSame topicGold and Silver Nanoparticles Synthesis and ApplicationsFrench-language works237,207