Effect of Mg addition of microstructure of 319 type alloys
Bibliographic record
Abstract
A. M. Samuel*a, H. W. Dotyb, S. Valtierrac & F. H. Samuelaa Université du Québec a ChicoutimiChicoutimi, Que., Canadab Materials EngineeringGeneral Motors, 823 Joslyn Avenue, Pontiac, MI 48340, USAc Corporativo Nemak S.A. DE C.V., PO Box 100, Garza Garcia, N.L. 66221, Mexico* Corresponding author, email Fawzy-Hosny_Samuel@uqac.caAbstractThe present study was undertaken to investigate the effect of Mg on the occurrence of incipient melting in experimental and industrial 319 alloys using thermal analysis, tensile testing, microstructural analysis and porosity measurements. Castings were prepared from experimental and industrial alloy melts containing Mg levels of 0–0·6 wt-%. The addition of Mg leads to the segregation of the copper phase, resulting in the formation of the block-like form of the CuAl2 phase rather than its finer eutectic-like form. This makes it more difficult to dissolve the CuAl2 phase during solution heat treatment. The addition of Mg to 319 alloy, irrespective of the alloy source, modifies the Si particle morphology. This effect is observed very clearly at 0·6 wt-%Mg, with a corresponding decrease in the Al–Si eutectic temperature compared to the base alloy. As expected, the modification effect of Mg is not very obvious at low Mg addition. The addition of Mg also leads to the precipitation of the Al5Mg8Cu2Si6 phase. This phase normally precipitates after the CuAl2 phase. Nevertheless, when the addition of Mg exceeds 0·4 wt-%, the precipitation of the Al5Mg8Cu2Si6 phase also takes place in another reaction, before the precipitation of the CuAl2 phase. The morphology of the Al5Mg8Cu2Si6 phase particles in this case is script-like rather than the irregular shaped particles normally observed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".