Novel Mg-Bi-Mn wrought alloys: The effects of extrusion temperature and Mn addition on their microstructures and mechanical properties
Bibliographic record
Abstract
Designing and developing the Mg alloys with low cost and high performance is of the great significance. Novel Mg-1Bi-xMn (x = 0, 1 and 2 wt.%) extruded alloys, in this work, were fabricated at different extrusion temperatures (220, 250 and 300 °C). The effects of extrusion temperature and Mn addition on the microstructures and mechanical properties of extruded alloys at room temperature were investigated. The results showed that decreasing the extrusion temperature could refine the average grain size, weaken the basal fiber texture intensity and improve the microstructural homogeneity of extruded alloys. When the Mn element was added to the Mg-1Bi alloy, the average grain size further reduced. Simultaneously, the number fraction of low angle grain boundaries (LAGBs) increased, along with the occurrence of regions without dynamic recrystallization (unDRX). The combined effects of grain refinement and coarse unDRXed structure made the textures of the extruded Mg-1Bi-xMn alloys never obviously change. Besides few large size un-dissolved second phases, fine Mg3Bi2 and α-Mn phases were precipitated in the extruded Mg-1Bi-xMn alloys and partial nano-scale α-Mn particles pined at grain boundaries (GBs) to effectively impede the migration of GBs for grain refinement. Microstructural variations determined the extruded Mg-1Bi-2Mn alloy to exhibit the highest yield strength of ∼ 319.2 MPa with the appropriate elongation-to-failure of ∼ 13% at the extrusion temperature of 220 °C, and they enabled the extruded Mg-1Bi-1Mn alloy to show the highest elongation-to-failure of ∼ 26% without the obvious loss of yield strength of ∼ 252.1 MPa.
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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".