Repassivation of a high chromium stainless steel orthopaedic alloy.
Bibliographic record
Abstract
The repassivation of Ortron90, a high chromium stainless steel alloy, was studied to assess the effect of passive layer removal on corrosion levels. Cathodic dissolution of the passive layer followed by potentiostatic experiments within the passive region were employed to study the repassivation process. The scratch method, carried out for comparison purposes, yielded current densities similar to those obtained by cathodic dissolution. The detailed analysis of the slopes of plots of log I/log t indicated that the repassivation did not follow any of the existing growth models. It also suggested that the slope depended on the extent of repassivation and reached a minimum when three to five monolayers of oxide were completed. The virtual potentiodynamic plots suggested the presence of some form of protective layer within 5-10 seconds and the change in open circuit potential vs time indicated that the passive layer present after 10 seconds of repassivation continued to evolve for about 1000 to 1500 seconds possibly representing a transition between two different forms such as oxide and a oxyhydroxides. Estimation of the effect of localized removal of passive layer on the corrosion indicated a dramatic increase in local corrosion density. These results show that a fast repassivation rate is an important requirement for biocompatibility of alloys used to manufacture dental and orthopaedic devices.
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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 | 0.000 | 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".