Icephobic Behavior of UV-Cured Polymer Networks Incorporated into Slippery Lubricant-Infused Porous Surfaces: Improving SLIPS Durability
Bibliographic record
Abstract
Ice accretion causes damage on power generation infrastructure, leading to mechanical failure. Icephobic materials are being researched so that ice buildup on these surfaces will be shed before the weight of the ice causes catastrophic damage. Lubricated materials have imposed the lowest-recorded forces of ice adhesion, and therefore lubricated materials are considered the state-of-the-art in this area. Slippery lubricant-infused porous surfaces (SLIPS) are one type of such materials. SLIPS are initially very effective at repelling ice, but the trapped fluid layer that affords their icephobic properties is easily depleted by repeated icing/deicing cycles, even after one deicing event. UV-cured siloxane resins were infused into SLIPS to observe effects on icephobicity and durability. These UV-cured polymer networks enhanced both the icephobicity and longevity of the SLIPS; values of ice adhesion below 10 kPa were recorded, and appreciable icephobicity was maintained up to 10 icing/deicing cycles.
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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".