Mechanical Performance of Zr‐Containing 354‐Type Al‐Si‐Cu‐Mg Cast Alloy: Role of Additions and Heat Treatment
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Bibliographic record
Abstract
In this article, the volume fraction of intermetallic compounds in Zr‐containing 354‐type Al‐Si‐Cu‐Mg alloys, characteristics of eutectic Si particles, and tensile, hardness, and impact properties have been evaluated with varying Ni and Mn contents and combination. The results revealed that additions of Ni and Mn in different amounts and combinations increased the volume fraction of intermetallic compounds in the tailored alloys, compared to the base alloy (cf. 12.21% for 4% Ni‐containing alloy with 2.5% for base alloy), producing a significant effect on the mechanical performance. The proposed additions enhanced the mechanical performance of the alloys, namely, the ambient‐ and elevated‐temperature tensile properties, hardness values, and impact properties. For the Mn‐containing alloys, the improvement in properties was attributed to the formation of sludge particles in the form of blocky α ‐Al 15 (Fe,Mn) 3 Si 2 alongside the script‐like α ‐iron phase that resisted crack propagation. The precipitation of Ni‐bearing phases such as Al 9 FeNi, Al 3 CuNi, and Al 3 Ni in the Ni‐containing alloys improved the mechanical properties through hindering cracks propagation. Interestingly, addition of 0.75 wt.% Mn to the base alloy proved to be competitive in strength values to the addition of 2 and 4 wt.% Ni, and better in terms of ductility values. The investigations showed that the variations in hardness and impact values follow the same trend as variations in the percentage volume fraction of intermetallic compounds, i.e., maximum property value is associated to the alloy with highest volume fraction of intermetallic compounds. Furthermore, the impact properties showed higher dependency on Al 2 Cu phase particles rather than the eutectic Si particles.
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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 | 0.001 |
| 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 it