Drag reduction on laser-patterned hierarchical superhydrophobic surfaces
Why this work is in the frame
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Bibliographic record
Abstract
Hierarchical laser-patterned surfaces were tested for their drag reduction abilities. A tertiary level of surface roughness which supports stable Cassie wetting was achieved on the patterned copper samples by laser-scanning multiple times. The laser-fabricated micro/nano structures sustained the shear stress in liquid flow. A rheometer setup was used to measure the drag reduction abilities in term of slip lengths on eight different samples. A considerable increase in slip length (111% on a grate sample) was observed on these surfaces compared to the slip length predictions from the theoretical and the experimental models for the non-hierarchical surfaces. The increase in slip lengths was correlated to the secondary level of roughness observed on the patterned samples. The drag reduction abilities of three different arrangements of the surface features were also compared: posts in a square lattice, parallel grates, and posts in a hexagonal lattice. Although the latter facilitates a stable Cassie state, it nevertheless resulted in a lower normalized slip length compared to the other two arrangements at a similar solid fraction. Furthermore, we coated the laser-patterned surfaces with a silane to test the effect of surface chemistry on drag reduction. While the contact angles were surprisingly similar for both the non-silanized and the silanized samples, we observed higher slip lengths on the latter, which we were able to explain by measuring the respective penetration depths of the liquid-vapour interface between surface features.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.017 | 0.031 |
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 it