Wetting of Rough Surfaces by a Low Surface Tension Liquid
Bibliographic record
Abstract
Abstract There exist textured surfaces that demonstrate large advancing contact angles when the expected behavior is complete wetting due to high Wenzel roughness. The roughness can represent an impediment to the motion of the contact line, leading to the possibility of contact line pinning and thus increased advancing contact angle. A set of fabricated textured surfaces with varying pillar diameters and pillar spacing were tested using hexadecane. Because of the low surface tension of hexadecane, the majority of the surfaces exhibited penetration of the liquid into the roughness, also known as the Wenzel state. Because of this penetration, the empirical pinning force framework we previously developed for wetting behavior on smooth surfaces and surfaces with texture where liquid does not penetrate the roughness was expanded to include the Wenzel state. For the surfaces that had Wenzel wetting, the receding contact angle tended to follow the predictions of the Wenzel equation, while the advancing contact angle tended to increase with increasing roughness when according to the Wenzel equation it would be expected to decrease. For surfaces where nonpenetrated Cassie wetting was observed, a constant high advancing contact angle and a receding contact angle that follows the trend predicted by the Cassie equation were observed.
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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) | 0.003 | 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".