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Control of particle size and surface properties of fluorinated acrylate microemulsion

2012· article· en· W2015796003 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSurface Engineering · 2012
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsMicroemulsionMaterials scienceAcrylateParticle sizePolyethylene glycolEmulsion polymerizationMethacrylateMethyl methacrylateFourier transform infrared spectroscopyEmulsionChemical engineeringPolymer chemistryButyl acrylateNanoparticleNuclear chemistryPolymerizationPolymerCopolymerChemistryComposite materialPulmonary surfactantNanotechnology

Abstract

fetched live from OpenAlex

Fluorinated acrylate microemulsion was prepared via co-polymerising methyl methacrylate, butyl acrylate and dodecafluoroheptyl methacrylate that were stabilised by polyethylene glycol mono- p-nonyl phenyl ether and sodium dodecyl benzene sulphonate and initiated by potassium persulphate. Many factors, which had an influence on the particle size and its distribution, had been investigated. It was possible to produce nanoparticles <100 nm and with narrower size distributions using the semicontinuous seeded emulsion polymerisation. Fourier transform infrared spectroscopy confirmed the structure of the microemulsion. The appearance of the microemulsion was translucent and accompanied with blue fluorescence. The stability of the microemulsion was very high. The solid content of the microemulsion was 38·65%. The contact angle of the film was not very high.

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.

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 score0.011
Threshold uncertainty score0.458

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 head0.013
GPT teacher head0.200
Teacher spread0.187 · 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