Superhydrophobic laser-ablated stainless steel substrates exhibiting Cassie–Baxter stable state
Bibliographic record
Abstract
In order to produce long-lasting, non-wettable surfaces, femtosecond laser ablation process was used to produce micro/nano structures on metallic surfaces. The effects of femtosecond laser irradiation process parameters (fluence, scanning speed and laser beam overlap) on the hydrophobicity of the resulting micro/nano-patterned morphologies on stainless steel were studied in detail. Seven distinctly different micro/nano patterns, namely nano-rippled, paraboloidal, sinusoidal, triple roughness, cauliflowered, tulip and scaly patterns, were fabricated. The latter pattern (scaly) was found to be identical to that of the butterfly wing structure. All patterns were classified according to laser intensity and scanning speed. Consequently, the fabricated substrates were chemically treated by silanization (Young contact angle (CA) of about 105°) in order to examine the additional effects of nanopatterning on wettability. The analysis of wettability revealed enhanced superhydrophobicity for most of these structures, particularly for the cauliflowered and scaly patterns with CAs in excess of 160° and contact angle hysteresis of less than 10°. Finally, the cauliflowered pattern was found to possess a stable composite state, which is important for certain applications such as friction (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".