Fabrication of superhydrophobic coatings based on nanoparticles and fluoropolyurethane
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".