Superhydrophobicity from the Inside
Bibliographic record
Abstract
The nature of trapped air on submersed ultra-water-repellent interfaces has been investigated. These gaseous layers (plastrons) can last from hours to, in some examples such as the Salvinia molesta fern, months. The interface of submerged superhydrophobic surfaces with carefully controlled micropatterned surface roughness has been probed using synchrotron-based high-resolution X-ray phase tomography. This technique looks in situ, through the aqueous/gas interface in three dimensions. Long-term plastron stability appears to correlate with the appearance of scattered microdroplets <20 μm in diameter that are sandwiched within the 30 μm thick gaseous interfacial layer. These microdroplets are centered on defects or damaged sections within the substrate surface approximately 20-50 μm apart. Such irregularities represent heterogeneous micro/nano-hierarchical structures with varying surface structures and chemistry. The stability of microdroplets is governed by a combination of electrostatic repulsion, contact angle limitations, and a saturated vapor pressure, the latter of which reduces the rate of diffusion of gas out of the air layer, thus increasing underwater longevity. Homogenous surfaces exhibiting purely nano- or micro-regularity do not support such microdroplets, and, as a consequence, plastrons can disappear in <20 h compared with >160 h for surfaces with scattered microdroplets. Such behavior may be a requirement for long-term nonwetting in any system.
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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".