Thermoregeneration of Plastrons on Superhydrophobic Coatings for Sustained Antifouling Properties
Bibliographic record
Abstract
A popular and desirable function of superhydrophobic coatings is their remarkable ability to retain an entrapped layer of air, called a plastron, when submerged underwater. The drawback is that the air layer is short‐lived due to solvation into the surrounding liquid. While manipulating the solubility of gases using temperature is a possible approach, it generally requires inefficiently heating large volumes of water. Following the demonstrated ability to maintain air bubbles on superhydrophobic surfaces for drag reduction, this article introduces a novel method of extracting gas from water to replenish and stabilize the plastron on superhydrophobic surfaces for sustained antifouling abilities. This method involves locally heating the liquid surrounding a superhydrophobic coating, reducing gas solubility, and causing the gas to nucleate at the liquid–air interface. The approach requires a relatively low energy input, due to the small volume of locally heated water. With a constant supply of equilibrated water and minimal energy input, the plastron can survive indefinitely without the need for a mechanical delivery of air. The thermoregenerating superhydrophobic samples were shown to exhibit excellent antifouling behavior and inhibited diatom attachment over a period of 5 days.
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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 | 0.001 |
| 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".