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Record W1969174359 · doi:10.1366/000370207782597111

Micro-Raman Spectroscopy Study of Colloidal Crystal Films of Polystyrene—Gold Composites

2007· article· en· W1969174359 on OpenAlexaff
Yahia Djaoued, Simona Bǎdilescu, S. Balaji, Nader Seirafianpour, Ahmad Reza Hajiaboli, Ramin Banan Sadeghian, Katherine E. Braedley, Ralf Brüning, Mojtaba Kahrizi, Vo‐Van Truong

Bibliographic record

VenueApplied Spectroscopy · 2007
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsConcordia UniversityMount Allison UniversityUniversité de Moncton
Fundersnot available
KeywordsRaman spectroscopyScanning electron microscopeMaterials sciencePolystyreneRaman microscopeMonolayerNanoparticleColloidal goldMicroscopyAnalytical Chemistry (journal)Colloidal crystalColloidNanotechnologyComposite materialRaman scatteringChemistryOpticsPolymer

Abstract

fetched live from OpenAlex

Monolayers and multilayers of polystyrene (PS)-gold composite films prepared by two different deposition methods have been investigated by atomic force microscopy (AFM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and confocal Raman microspectroscopy. The intensity of the 1001 cm(-1) ring breathing mode of PS is used to evaluate the degree of ordering of monolayers and multilayers within a colloidal crystal. The depth profiling capability of confocal Raman microscopy is used to probe the regions inside the fractures in multilayered films. The intensity profile of the 1001 cm(-1) peak revealed the presence of fractures of different shapes with some PS microspheres at the bottom of the fracture. A strong increase in the Raman intensity (by 10(3) times) has been observed when probing the regions where Au nanoparticles are concentrated in aggregates of different shapes. This enhancement is attributed to the surface plasmons generated by the periodic structure of the gold nanoparticles.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.250
Teacher spread0.241 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

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