Electrochemical Passivation of a Biomedical-Grade 316LVM Stainless Steel
Bibliographic record
Abstract
Abstract The present work aimed at developing a simple electrochemical passivation method for a biomedical-grade stainless steel 316LVM in order to increase its pitting corrosion resistance. The results showed that the passivation of 316LVM by employing a cyclic potentiodynamic polarization method can provide a significant improvement in pitting corrosion resistance of the material. A complete absence of pitting in physiological solutions was achieved. Even at significantly higher concentrations of chlorides, relevant to marine and industrial applications, an improvement in pitting potential by ca. 870 mV was observed. An increase in temperature during the passivation process did not have a significant effect on the resulting passive film pitting corrosion resistance, while an increase in temperature of the testing solution resulted in a significant decrease in the pitting corrosion resistance of the material investigated. The results suggest that both a change in dielectric properties of the passive film and its enrichment in chromium are responsible for the observed improvement in corrosion resistance. A mechanism of the passive film pitting breakdown was proposed.
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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".