Hydrophobic Surface Fabrication of Metallic Materials
Bibliographic record
Abstract
The super-hydrophobic property of the surface is attracting attention as it can solve the problems of many existing surface treatment fields. In order to realize this characteristic, many researchers have attempted to increase the super-hydrophobicity of the surface by fabricating surface structures of various shapes using MEMS.[2-3] The superhydrophobic surface may have advantages in drag reduction[4], antifouling[5], anti-corrosion[6], self-cleaning, anti-icing and de-icing. If these waterproof properties are applied to aluminum alloys, which are widely used as metal materials[7], it will be effective for problems such as surface aging, pollution and corrosion. Therefore, in this study, the surface of the aluminum metal has proposed a method for fabricating a super-hydrophobic surface using an aluminum anodization process and nickel electroplating. In order to fabricate a nano-hole structure on the surface of an aluminum plate, a nano-hole array support template was fabricated through a two-step aluminum anodization process. As the anodizing process conditions, 0.1 M sulfuric acid was used as an electrolyte. The process temperature was 0C and the applied voltage was 20V. After the first process, all of the aluminas were etched using a phosphoric acid-chromic acid mixed solution at 35C. The second process was performed under the same conditions as the first process. The fabricated nano-hole array was measured to be the diameter 258 nm and the interpore 5711 nm. The fabricated alumina nano-hole array template was filled with nickel through the nickel electroplating method to form a nickel-alumina tree shape. Electroplating process conditions were carried out using an AC@10V@50Hz power supply using an electrolyte based on nickel sulfate, nickel chloride, and boric acid. The alumina hole array used as a servo was removed by etching. As a result of measuring the contact angle of the fabricated surface, it was confirmed that the surface had an angle of 135 or more, and thus had a super-hydrophobic surface. However, the tree shape collapsed or disappeared in some areas. It is understood that this is lost during the etching process.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".