Degradation Behaviour of Metallic Biomaterials for Degradable Stents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The short-term need of scaffolding function of stent and the prevention of potential longterm complication of permanently implanted stent have directed to the original idea of biodegradable stent. Selecting and developing materials showing appropriate mechanical and degradation properties are key steps for the development of this new class of medical devices. Therefore, the study of their in vitro degradation behaviour is mandatory for the selection of potential candidate materials suited in vivo. In this work, the degradation behaviour of current studied biodegradable metals including three magnesium alloys (Mg, AM60B and AZ91D), pure iron and Fe-35Mn was investigated. The tests were performed in a simulated blood plasma solution at 37±0.1 oC, using three different methods; potentiodynamic polarization, static immersion, and dynamic test in a test-bench which mimics the flow condition in human coronary artery. Degradation rate was determined as ion release rate measured by using atomic adsorption spectroscopy (AAS) and also estimated from weight loss and corrosion current. Surface morphology and chemical composition of corroded specimens were analyzed by using SEM/EDS. The three degradation methods provide consistent results in corrosion tendency, where Mg showed the highest corrosion rate followed by AZ91D, AM60B, Fe-35Mn and iron. Potentiodynamic polarization gives a rapid estimation of corrosion behaviour and rate. Static immersion test shows the effect of time on the degradation rate and behaviour. Dynamic test provides the closest approach to the environment after stent implantation and its results show the effect of the flow on the materials degradation. In conclusion, the three investigated methods can be applied for screening, selecting and validating materials for degradable stent application before going further to in vivo assessments.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 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 it