Cooling, Microstructure and Properties of Permanent Steel Mold Cast Wrought AZ80 Alloy with Varying Casting Wall Sizes
Bibliographic record
Abstract
The wrought magnesium alloy AZ80, comprising 8 wt% aluminum, underwent fabrication via permanent steel mold casting (PSMC), involving three distinct stages with wall sizes measuring 6 mm, 10 mm, and 20 mm. The numerical simulation of the solidification showed that the cooling rate of the step casting increased, when the wall size decreased. The as-cast alloy's microstructure underwent scrutiny through optical microscopy and scanning electron microscopy (SEM), complemented by energy dispersive spectroscopy (EDS) analysis. Findings from the microstructure examinations unveiled the presence of primary Mg phase across all three sections of the cast AZ80 alloy, accompanied by micron and nanosized Mg-Al-Zn intermetallic phases, as well as micron-sized Al-Mn intermetallic phases. But the intermetallic contents increased, and the dendrite sizes and the porosity levels decreased, as the wall sizes reduced. The tensile testing results revealed significant findings regarding the ultimate tensile strength (UTS), yield strength (YS), modulus, resilience, and toughness, increased, when the wall sizes decreased to 6 from 20 mm. The negative effect of large casting wall sizes on ductility was demonstrated. Exceptional tensile properties of the thin wall resulted from fine dendritic structure, high intermetallic content, and minimal porosity level.
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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".