Mechanical Performance and Precipitation Behavior in Al-Si-Cu-Mg Cast Alloys: Effect of Prolonged Thermal Exposure
Bibliographic record
Abstract
Al-Si-Cu-Mg cast (354) alloys are used in the automotive sector owing to their remarkable properties which are achievable after applying appropriate thermal treatments. Zirconium, Nickel, and Manganese were added to this category of Al-alloys to preserve good mechanical properties while being exposed to elevated temperatures for long times. The ultimate and yield strength values obtained at room temperature for the stabilized (thermally-exposed) T5-treated condition were comparable to those of the stabilized T6-treated condition, whereas the same properties for T5-treated alloys were higher than those of T6-treated ones for elevated-temperature tensile testing. Interestingly, the results showed that the addition of 0.75 wt.% Mn was competitive with the addition of 2 and 4 wt.% Ni with respect to the elevated-temperature and ambient temperature strength values, respectively. In addition, the Mn-containing alloy M3S exhibited improved ductility values at ambient temperature and at 250 °C, compared to the Ni-containing alloys. Examination of the fracture surface of tested samples revealed the advantageous role of sludge particles in enhancing the performance of Mn-containing alloys through their resistance to the propagation of cracks that developed in many intermetallic phases. This finding is considered to be economically significant in view of the lower price of manganese compared to that of nickel.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".