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Record W2075027657 · doi:10.1021/la702503m

Particle−Particle Interactions and Chain Dynamics of Fluorocarbon and Hydrocarbon Functionalized ZrO<sub>2</sub> Nanoparticles

2008· article· en· W2075027657 on OpenAlexafffund
Andrew O'Donnell, Kimberly Yach, Linda Reven

Bibliographic record

VenueLangmuir · 2008
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFluorocarbonFumed silicaHydrocarbonNanoparticleAdsorptionChemistryMonolayerParticle (ecology)Chemical engineeringMolecular dynamicsChemical physicsCrystallographyMaterials scienceOrganic chemistryNanotechnologyComputational chemistry

Abstract

fetched live from OpenAlex

The chain conformation and dynamics of hydrocarbon and perfluorocarbon fatty acids adsorbed on 4 nm ZrO2 particles were characterized by solid-state 13C chemical shift and 19F NMR relaxation measurements, respectively, and compared to those from previous studies on lower surface area fumed metal oxide powders. The interdigitation of chains between neighboring particles, which increases with chain length, can be detected from the splitting of the 13C NMR and 19F NMR signals of the CH3 and CF3 groups, respectively. Similar to the case of alkanethiol self-assembled monolayers (SAMs) on gold nanoparticles, this interdigitation allows for efficient chain packing despite the high surface curvature. The hydrocarbon chains on the ZrO2 nanoparticles are more ordered, and the reversible chain length dependent order-disorder transition temperatures are elevated relative to those of the same fatty acids adsorbed on fumed ZrO2 powder. Likewise, the 19F spin lattice relaxation times of the fluorocarbon chains approach those of the bulk acids with increasing chain length and interdigitation, indicating densely packed chains.

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 score0.241
Threshold uncertainty score0.436

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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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

Citations15
Published2008
Admission routes2
Has abstractyes

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