Icephobic PTFE coatings for wind turbines operating in cold climate conditions
Bibliographic record
Abstract
A new treatment offers a simple and inexpensive method to reduce considerably ice adhesion on a wind turbine blade surface ensuring a safe and reliable energy production during winter periods. This treatment has icephobic characteristics, satisfactory mechanical, optical and electrical properties and doesn't alter the surface appearance. The technique consists in depositing a poly(tetrafluoroethylene) or PTFE coating, which strongly clings on a high porosity blade surface. A uniform coating was obtained by dipping the blade samples in a PTFE solution dispersion followed by annealing at 290°C for 2 min in an argon atmosphere. The resulting film yielded a contact angle around 145°, a hysteresis of 30°, a surface tension estimated to 11.7 mN/m and a slipping angle of 45° even at temperature as low as -6°C. The shear strength of ice adhesion was reduced by 80% compared to pristine blade surface at temperatures ranging from -1.8°C to -12.5°C. There was no observed effect of ice shedding events and no accelerated aging was observed through UVC irradiation and corrosive acidic solution on the hydrophobicity of the coated surface. The low surface energy of that coating is promising for its use in the wind turbine industry.
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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".