Annealing and ultraviolet treatment of plasma fluorocarbon films for enhanced cohesion and stability
Bibliographic record
Abstract
Abstract Stents, commonly used for the treatment of cardiovascular diseases, are mainly made of 316L stainless steel. They are, however, prone to corrosion when they are in contact with human body fluid. To prevent this corrosion process and to ameliorate their patencies, in this study, we used a strategy to cover stent materials with a protective fluorocarbon layer deposited by plasma polymerization. In an approach to optimize its cohesion properties and stability, posttreatments, namely, thermal annealing and UV irradiation, were applied on the ultrathin fluorocarbon film. A combination of X‐ray photoelectron spectroscopy, polarized near‐edge X‐ray absorption fine‐structure spectroscopy, and time‐of‐flight secondary ion mass spectrometry demonstrated that UV treatment led to chain scission and film crosslinking and, in this way, decreased the amount and/or size of nanoscaled defects originally present in the films. Annealing on the other hand induced a film reorganization in favor of longer, well‐ordered fluorocarbon chains. However, a deformation process that was applied to study the film adhesion properties induced chain scissions with reorganization. Aging tests exhibited an oxidation of the top‐most layer for both the as‐deposited and posttreated samples. Finally, the film stability was improved after UV treatment for both the nondeformed and deformed samples. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".