Wettability of biomimetic thermally grown aluminum oxide coatings
Bibliographic record
Abstract
In this paper, wettability behavior of a rough but intrinsically hydrophilic oxide ceramic, formed via simple thermal oxidation of a commercial metallic alloy in laboratory air, has been analyzed. Drop shape analysis (DSA) revealed static water contact angles for the rough ceramic surfaces up to 128° (greater than for Teflon™). We propose the high apparent contact angles to be a result of surface roughening via the morphological changes of the oxide scale with oxidation conditions. The surface morphological changes occurring during the growth of the oxide film resulted in the formation of vertical platelets that ably shifted the wetting behavior from a Wenzel to an unstable Cassie-Baxter state. The platelet morphology of the ceramic resembles the structure of epicuticular waxes on certain species of superhydrophobic leaves. Moreover, surface textures for very short oxidation times were also found to increase hydrophilicity in the scale and reduce the contact angle by imparting a Wenzel state. Various characterization techniques (XRD, XPS, and SEM) were performed in order to detect the crystallographic phases in the scales, analyze carbon content and determine the morphology of the oxide layer. Morphological features of the oxide platelets were quantified and platelet width, spacing and height were found to correlate well with the apparent contact angle trend as a function of oxidation time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".