Fabrication and Wettability Analysis of Hydrophobic Stainless Steel Surfaces With Microscale Structures From Nanosecond Laser Machining
Bibliographic record
Abstract
In this work, nanosecond laser machining is used to fabricate hydrophobic 17-4 PH stainless steel surfaces with microscale and submicron structures. Four surface structures were designed, with microscale channels and pillars (100 μm pitch size) of uniform heights (100 μm) or alternating heights (between 100 μm and 50 μm). During fabrication, the high-power laser beams also created submicron features on top of the microscale ones, leading to hierarchical, multiscale surface structures. Detailed wettability analysis was conducted on the fabricated samples. Measured static contact angles of water on these surfaces are over 130 deg without any coating, compared to ∼70 deg on the original steel surface before laser machining. Slightly lower contact angle hysteresis was also observed on the laser machined surfaces. Overall, these results agree with a simple Cassie–Baxter model for wetting that assumes only fractional surface area contact between the droplet and the surface. This work demonstrates that steel surfaces machined with relatively inexpensive nanosecond laser can achieve excellent hydrophobicity even with simple microstructural designs.
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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) | 0.000 | 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".