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Record W2045830953 · doi:10.1002/app.38418

Fabrication of superhydrophobic coatings based on nanoparticles and fluoropolyurethane

2012· article· en· W2045830953 on OpenAlex
S.A. Seyedmehdi, Hui Zhang, Jesse Zhu

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

VenueJournal of Applied Polymer Science · 2012
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsWestern University
Fundersnot available
KeywordsFluoropolymerContact angleMaterials scienceNanoparticleFabricationComposite materialHysteresisDurabilityNanocompositePolymerNanotechnology

Abstract

fetched live from OpenAlex

Abstract Hydrophobic nanosilica or nanofluoric particles were mixed with fluoropolyurethane resin to fabricate superhydrophobic coatings that have contact angles higher than 145°. These coatings were prepared from the simple mixing of nanoparticles in fluoropolymer and were cured at room temperature. Different fractions of nanosilica, nanofluoric particles, and the combination of them were used to find the best formulations of superhydrophobic coatings. Contact angle, contact angle hysteresis, sliding angle, hardness, and UV durability tests were conducted to find the effectiveness of these coatings. The results showed that only fluoropolyurethane coatings containing nanosilica or the combination of it and fluoric particles were superhydrophobic. Also, the hardness of coatings was increased by raising nanoparticle concentrations. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013

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)0.002
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 score0.002
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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