Effect of grain sizes on mechanical properties and biodegradation behavior of pure iron for cardiovascular stent application
Bibliographic record
Abstract
Pure iron has been demonstrated as a potential candidate for biodegradable metal stents due to its appropriate biocompatibility, suitable mechanical properties and uniform biodegradation behavior. The competing parameters that control the safety and the performance of BMS include proper strength-ductility combination, biocompatibility along with matching rate of corrosion with healing rate of arteries. Being a micrometre-scale biomedical device, the mentioned variables have been found to be governed by the average grain size of the bulk material. Thermo-mechanical processing techniques of the cold rolling and annealing were used to grain-refine the pure iron. Pure Fe samples were unidirectionally cold rolled and then isochronally annealed at different temperatures with the intention of inducing different ranges of grain size. The effect of thermo-mechanical treatment on mechanical properties and corrosion rates of the samples were investigated, correspondingly. Mechanical properties of pure Fe samples improved significantly with decrease in grain size while the corrosion rate decreased marginally with decrease in the average grain sizes. These findings could lead to the optimization of the properties to attain an adequate biodegradation-strength-ductility balance.
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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".