Rf-Sputtered Teflon®-Modified Superhydrophobic Nanostructured Titanium Dioxide Coating on Aluminum Alloy for Icephobic Applications
Bibliographic record
Abstract
Icing on surfaces such as cables or high-voltage insulators may often lead to severe safety issues such as power outages in cold winter conditions. Conventional methods used to tackle such icing problems include mechanical deicing, where the ice is scraped or broken, and chemical deicing, where deicers such as ethylene glycol are used. However, the best approach to addressing these issues is to prevent ice formation in the first place. Research in the past few decades have shown hydrophobic and superhydrophobic surfaces to be effective in reducing ice adhesion. We used the concept of water repellency to turn an aluminum surface superhydrophobic to minimize ice adhesion on these surfaces. However, to render these surfaces also applicable to insulating surfaces, we also demonstrated the adaptability of the concept on a low dielectric oxide, TiO2, to an aluminum surface with icephobic properties. This work demonstrates the importance of the coexistence of rough nanostructures as well as low-surface-energy compositions on a surface to make it superhydrophobic and icephobic and is applicable on metals and insulating surfaces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".