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Record W2313868415 · doi:10.1021/la202815g

Light-Activated Covalent Formation of Gold Nanoparticle–Graphene and Gold Nanoparticle–Glass Composites

2011· article· en· W2313868415 on OpenAlexaff
Hossein Ismaili, Dongsheng Geng, Andy Xueliang Sun, Trissa T. Kantzas, Mark S. Workentin

Bibliographic record

VenueLangmuir · 2011
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsColloidal goldNanoparticleMaterials scienceGrapheneCovalent bondComposite materialNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Monolayer protected gold nanoparticles (AuNPs) modified with a 3-aryl-3-(trifluoromethyl)diazirine functionality at its terminus (Diaz-AuNPs, 3.9 nm) were prepared and irradiated in the presence of two very different substrates, reduced graphene and glass. Upon irradiation, the terminal diazirine group loses nitrogen to generate a reactive carbene at the interface of the AuNPs that can then undergo addition or insertion reactions with functional groups on the graphene or glass surfaces, leading to the formation of graphene-AuNP and glass-AuNP hybrids, respectively. The AuNP hybrids were characterized using TEM, XRD, XPS, AFM, and UV-vis spectroscopy. Control experiments done in the absence of irradiation demonstrate that carbene activation is required for incorporation of significant AuNP onto the materials. The AuNP hybrids are robust and stable to excessive washing and centrifugation supporting the covalent nature of the interaction between the AuNP and the graphene or silicate glass substrates. Because the formation of the composite is light activated, it lends itself to photopatterning; this application is demonstrated for making the glass-AuNP composites.

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 score0.454

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 head0.016
GPT teacher head0.198
Teacher spread0.182 · 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

Citations73
Published2011
Admission routes1
Has abstractyes

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