Smart low interfacial toughness coatings for on-demand de-icing without melting
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.
Bibliographic record
Abstract
Ice accretion causes problems in vital industries and has been addressed over the past decades with either passive or active de-icing systems. This work presents a smart, hybrid (passive and active) de-icing system through the combination of a low interfacial toughness coating, printed circuit board heaters, and an ice-detecting microwave sensor. The coating's interfacial toughness with ice is found to be temperature dependent and can be modulated using the embedded heaters. Accordingly, de-icing is realized without melting the interface. The synergistic combination of the low interfacial toughness coating and periodic heaters results in a greater de-icing power density than a full-coverage heater system. The hybrid de-icing system also shows durability towards repeated icing/de-icing, mechanical abrasion, outdoor exposure, and chemical contamination. A non-contact planar microwave resonator sensor is additionally designed and implemented to precisely detect the presence or absence of water or ice on the surface while operating beneath the coating, further enhancing the system's energy efficiency. Scalability of the smart coating is demonstrated using large (up to 1 m) iced interfaces. Overall, the smart hybrid system designed here offers a paradigm shift in de-icing that can efficiently render a surface ice-free without the need for energetically expensive interface melting.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it