Plasma Surface Modification of 316L Stainless Steel for Cardiovascular Stent Coating
Bibliographic record
Abstract
Coronary stents are metallic (316L stainless steel) devices employed during balloon angioplasty to reopen and prevent the re-obstruction of a diseased narrowed area within a coronary artery. To reduce restenosis rate, bare metal stent coating is a promising solution. The coating can act as an anticorrosive barrier against the aggressive properties of biological environment, improving the long-term safety of the device. The goal of this study is to develop a dry process to isolate metallic surface from the biological environment by depositing a thin plasma polymerized allylamine (CH2=CH-CH2-NH2) film on the metallic surface. Plasma polymerized allylamine films were deposited on flat electropolished 316L stainless steel samples in a low pressure plasma reactor (70 kHz). Chemical composition of the coatings has been analysed as a function of the discharge power and treatment time. Moreover, special attention has been paid on the stability of the coating after immersion during 24 hours in D.I. water. Finally, to mimic stent expansion conditions, a “small punch test” has been used to investigate the adhesive properties of the coating. Our results demonstrate that is possible to deposit a stable, cohesive and adhesive plasma polymerized allylamine thin film which can be used as a coating for cardiovascular stents
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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".