Effect of laser welding on the mechanical and degradation behaviour of Fe-20Mn-0.6C bioabsorbable alloy
Bibliographic record
Abstract
The present work aims at exploring the influence of laser welding on the functional behaviour of a Fe-20Mn-0.6C (wt.%) bioabsorbable alloy. At first, the selection of the most suitable process speed (40 mm/s) was done in order to obtain a full penetration joint with limited taper. Then, microstructural and mechanical analyses of welded sheets confirmed suitable performance of the joint, without porosity, thus preserving chemical composition, mechanical resistance and ductility even after welding. In particular, the base material comprised both γ austenite and ε martensite, while the welded samples showed a further type of martensite, namely α’. Moreover, ultimate tensile strength (1095 MPa and 1104 MPa in base and welded material, respectively) and elongation to failure (61.3% and 60.9%, respectively) were almost not influenced by the welding process. Considering the absorbable nature of these alloys, static immersion degradation tests were carried out, and confirmed that the surface of the welded bead did not exhibit a significant variation of the material degradation rate after 14 days in modified Hanks’ solution. Finally, a significant accumulation of degradation products, mainly (Fe,Mn)CO3, was observed along the joining line.
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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) | 0.001 | 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".