Impact of Droplet Wettability on Scanning Electrochemical Cell Microscopy Performance in Stainless Steels
Bibliographic record
Abstract
Variations in droplet wettability affect localized corrosion during scanning electrochemical cell microscopy (SECCM) on stainless steel. The droplet dynamics are influenced by stainless-steel microstructural features and surface conditions-such as surface roughness, inclusions, and the addition of an oil layer. As opposed to previous work on aluminum alloys, droplet spreading is promoted by oil immersion, which leads to an increase in the cathodic currents. Rougher surfaces hinder droplet spreading, largely due to the droplet pinning effect, and exhibit higher pitting corrosion incidences compared to smoother surfaces. Moreover, the presence of inclusions intensifies pitting initiation and constrains the landing area (droplet size). We report that while the landing area does not affect the number of metastable pits, small landing areas lead to a high probability of stable pitting.
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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 | 0.001 |
| 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 | 0.001 | 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".