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Record W2039036005 · doi:10.1021/la062886b

Two-Dimensional Self-Organization of Polystyrene-Capped Gold Nanoparticles

2007· article· en· W2039036005 on OpenAlexafffund
Hélène Yockell-Lelièvre, Jessie Desbiens, Anna M. Ritcey

Bibliographic record

VenueLangmuir · 2007
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPolystyreneMonolayerColloidal goldGraftingNanoparticleMaterials scienceSurface plasmon resonanceAbsorption (acoustics)PlasmonChemical engineeringAbsorption spectroscopyPolymer chemistryThermogravimetric analysisNanotechnologyPolymerComposite materialOptics

Abstract

fetched live from OpenAlex

Thiol end-functionalized polystyrene chains have been introduced onto the surface of gold nanoparticles via a two-step grafting-to method. This simple grafting procedure is demonstrated to be efficient for gold nanoparticles of different sizes and for particles initially dispersed in either aqueous or organic media. The method has been applied successfully for a relatively large range of polystyrene chain lengths. Grafting densities, as determined by thermogravimetric analysis, are found to decrease with increasing chain length. In all cases, the grafting density indicates a dense brush conformation for the tethered chains. The resulting functionalized nanoparticles self-organize into hexagonally ordered monolayers when cast onto solid substrates from chloroform solution. Furthermore, the distance between the gold cores in the dried monolayer is controlled by the molecular weight of the grafted polystyrene. Optical absorption spectra recorded for the organized monolayers show the characteristic plasmon absorption of the gold particles. Importantly, the plasmon resonance frequency exhibits a distinct dependence on interparticle separation that can be attributed to plasmon coupling between neighboring gold cores.

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 score0.270

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 head0.010
GPT teacher head0.232
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

Citations93
Published2007
Admission routes2
Has abstractyes

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