The Influence of Rare Earth Metals on the Microstructure and Mechanical Properties of 220 and 356.1 Alloys for Automotive Industry
Bibliographic record
Abstract
Application of rare earths (RE) as grain refiners is well-known in the technology of aluminum alloys for the automotive industry. In the current study, Al-2.4%Cu-0.4%Mg alloy (coded 220) and Al-7.5%Si-0.35%Mg alloy (coded 356.1), were prepared by melting each alloy in a resistance furnace. Strontium (Sr) was used as a modifier, while titanium boride (TiB2) was added as a grain refiner. Measured amounts of Ce and La were added to both alloys (max. 1 wt.%). The alloy melts were poured in a preheated metallic mold. The main part of the study was conducted on tensile testing at room temperature. The results show that although RE would cause grain refining to be about 30–40% through the constitutional undercooling mechanism, grain refining with TiB2 would lead to approximately 90% refining (heterogenous nucleation mechanism). The addition of high purity Ce or La (99.9% purity) has no modification effect regardless of the alloy composition or the concentration of RE. Depending on the alloy ductility, the addition of 0.2 wt.%RE has a hardening effect that causes precipitation of RE in the form of dispersoids (300–700 nm). However, this increase vanishes with the decrease in alloy ductility, i.e., with T6 treatment, due to intensive precipitation of ultra-fine coherent Mg2Si-phase particles. There is no definite distinction in the behavior of Ce or La in terms of their high affinity to interact with other transition elements in the matrix, particularly Ti, Fe, Cu, and Sr. When the melt was properly degassed using high-purity argon and filtered using a 20 ppi ceramic foam filter, prior to pouring the liquid metal into the mold sprue, no measurable number of RE oxides was observed. In conclusion, the application of RE to aluminum castings would only lead to formation of a significant volume fraction of brittle intermetallics. In Ti-free alloys, identification of Ce- or La-intermetallics is doubtful due to the fairly thin thickness of the precipitated platelets (about 1 µm) and the possibility that most of the reported Al, Si, and other elements make the reported values for RE rather ambiguous.
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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".