Interaction between Air Bubbles and Superhydrophobic Surfaces in Aqueous Solutions
Bibliographic record
Abstract
Superhydrophobic surfaces are usually characterized by a high apparent contact angle of water drops in air. Here we analyze the inverse situation: Rather than focusing on water repellency in air, we measure the attractive interaction of air bubbles and superhydrophobic surfaces in water. Forces were measured between microbubbles with radii R of 40-90 μm attached to an atomic force microscope cantilever and submerged superhydrophobic surfaces. In addition, forces between macroscopic bubbles (R = 1.2 mm) at the end of capillaries and superhydrophobic surfaces were measured. As superhydrophobic surfaces we applied soot-templated surfaces, nanofilament surfaces, micropillar arrays with flat top faces, and decorated micropillars. Depending on the specific structure of the superhydrophobic surfaces and the presence and amount of entrapped air, different interactions were observed. Soot-templated surfaces in the Cassie state showed superaerophilic behavior: Once the electrostatic double-layer force and a hydrodynamic repulsion were overcome, bubbles jumped onto the surface and fully merged with the entrapped air. On nanofilaments and micropillar arrays we observed in addition the formation of sessile bubbles with finite contact angles below 90° or the attachment of bubbles, which retained their spherical shape.
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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 | 0.001 |
| 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".