Characterisation and thermodynamic calculations of biodegradable Mg–2.2Zn–3.7Ce and Mg–Ca–2.2Zn–3.7Ce alloys
Bibliographic record
Abstract
In the present study, the effect of Ca (0.5–6 wt-%) content on the microstructure, phase formation, and mechanical properties and in vitro degradation behaviour of Mg–2.2Zn–3.7Ce alloys were investigated. Microstructural analysis and thermodynamic calculations also showed that Mg–2.2Zn–3.7Ce alloy contain α-Mg, Mg 12 Ce and CeMgZn 2 , while after adding 0.5 wt-% Ca to Mg–2.2Zn–3.7Ce alloy, IM1 (Ca 3 Mg x Zn 15− x ) (4.6 ≤ x ≤ 12) phase was detected. Further addition of Ca to 6 wt-% resulted in forming Mg 2 Ca besides α-Mg, Mg 12 Ce and IM1 with the absence of CeMgZn 2 . The tensile strength and elongation of the Mg–Ca–2.2Zn–3.7Ce alloys increase with increasing Ca content up to 1.5 wt-%, while further addition of Ca to 6 wt-% has a reversed effect. Similarly, the degradation rate of the alloys increased first with increasing Ca content and then decreased.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".