Superhydrophobicity of Natural and Artificial Surfaces under Controlled Condensation Conditions
Bibliographic record
Abstract
In this paper, we have comparatively investigated the stability of superhydrophobic behaviors of fresh and biomimetic lotus leaf surfaces under controlled water condensation conditions. The binary micro/nano structures of the superhydrophobic surfaces are observed with electron micrographs. Contact and sliding angles are evaluated by syringing water droplets on the substrates with surface temperatures and humidity precisely controlled between -10 and 30 °C, and RH = 10, 30, 60, and 90%. According to the calculations on the solid-liquid contact area fraction in different environmental conditions based on a micro/nano binary structure model, the effects of condensed water on superhydrophobic surfaces are assessed quantitatively. Both the calculated and experimental results indicate that the temperature difference between surface temperature and the dew point during measurement is essential to the occurrence of water condensation while the effect of condensation on the surface wettability also depends on the topology of hierarchical structured surfaces. The loss of water repellency that usually appears on the artificial superhydrophobic surface under low temperature and high humidity conditions is proved to be reversible, showing a bidirectional transition of the equilibrium state between Wenzel and Cassie-Baxter.
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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".