Development of biodegradable Fe-Mn thin structures by electroforming in deep eutectic solvents
Bibliographic record
Abstract
Fe-Mn alloys represent promising candidates for temporary biomedical intravascular implants with a thin structure (e.g., coronary, cerebral and peripheral stents) due to their high mechanical strength, acceptable biocompatibility, and controllable corrosion rate. Traditionally, these devices are produced by casting followed by thermo-mechanical processing, i.e. a time- and energy-intensive top-to-bottom approach. This study explores electroforming as an alternative method to fabricate bottom-to-top thin Fe-Mn structures using ethylene glycol-based deep eutectic solvents (DESs). Glycine was introduced as a complexing agent to enhance Mn co-deposition. Electroforming was investigated in presence of three glycine concentrations (0.2, 0.4, and 0.6 M), and the the microstructure, composition, corrosion behavior, and cytocompatibility of the developed thin (50-85 µm) structures were characterized. Higher glycine content improved Mn incorporation, crystallinity, hardness and increased corrosion rate. These findings support the use of DES-based electroforming as a promising route for fabricating biodegradable Fe-Mn devices with tunable properties.
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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".