Recoverable underwater superhydrophobicity from a fully wetted state via dynamic air spreading
Bibliographic record
Abstract
Maintaining the superhydrophobicity underwater offers drag resistance reduction, antifouling, anti-corrosion, noise reduction, and gas collection for boat hulls and submarine vehicles. However, superhydrophobicity typically does not last long underwater since the Cassie state is metastable. Here, we report a reversible and localized recovery of superhydrophobicity from the fully wetted state via air bubble spreading. Composed of sparse fluorinated chained nanoparticles, the submerged surface shows super-low energy barrier for bubble attachment. Especially the recovered plastron exhibits excellent longevity. Based on a simplified, truncated nanocone model, the dynamic spreading of bubbles is analyzed considering two basic parameters, i.e., surface geometric structure and surface energy (which appeared as intrinsic water contact angle). Numerical simulation results via COMSOL confirms the effect of geometric structure on bubble spreading. This investigation will not only offer new insights for the design of robust recoverable superhydrophobic surfaces but also broaden the applications of superhydrophobic coatings.
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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".