Microstructural Precipitation Evolution and In Vitro Degradation Behavior of a Novel Chill-Cast Zn-Based Absorbable Alloy for Medical Applications
Bibliographic record
Abstract
In recent years, increasing interest has been placed in the development of Zn alloys for absorbable biomedical applications. It has been demonstrated that these alloys are potential candidates for endovascular applications. In the present work, a novel Zn-12.5Ag-1Mg alloy was investigated as a potential biomedical absorbable material. As a reference, the exhibited biocompatible properties are compared with those of pure Zn and a Zn-1Mg alloy. All the alloys investigated in this work were cast in a water-cooled Cu-mold (chill casting). Subsequently, the alloys were solution-treated and then extruded. The microstructural evolution at each stage of the alloy processing was resolved by analytical means including optical, scanning, transmission microscopy, and X-ray diffraction. By these means, the various phases belonging to this alloy system were disclosed. In addition, determinations of both corrosion and mechanical properties were carried out in the proposed Zn-12.5Ag-1Mg alloy. In particular, an excellent combination of strength and ductility was found, which is attributed to grain refinement as well as the precipitation of a uniform distribution of refined phases (i.e., AgZn solid solution, ε-AgZn3, and Ag0.15MgZn1.85 intermetallics). All the precipitated intermetallics were embedded in a η-Zn matrix. As for the corrosion degradation in the physiological NaCl solution in the as-extruded condition, the experimental outcome indicates that the Zn-12.5Ag-1Mg alloy exhibits degradation rates far superior to currently reported ones for Zn-based alloys intended for absorbable biomedical applications.
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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) | 0.000 | 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".