Effect of Sr and Ni Addition on Microstructure, Tensile Behavior and Electrical Conductivity of Squeeze Cast Al-6Si-3Cu Al Alloy
Bibliographic record
Abstract
Mechanical strengths and electrical conductivity are the very important engineering properties of lightweight aluminum (Al) alloys used in automobiles, especially for battery-powered electric vehicles (BEV). However, the main issue is that the mechanical properties and the electrical conductivity of Al alloys are mutually exclusive. This study aims to simultaneously improve both the tensile properties and the electrical conductivity of the squeeze as-cast Al-6wt% Si-3wt% Cu by modifying its microstructure with the addition of nickel (Ni) and strontium (Sr). In comparison to those of the alloy free of Sr and Ni, the additions of 0.03 wt.% Sr and 0.5 wt.% Ni in the Al-6Si-3Cu alloy significantly improved the ultimate tensile strength, yield strength and electrical conductivity. This was because the addition of Ni element, as a transition element, collaborated with Cu to form fine intermetallic Al-Cu-Ni phases for dispersion strengthening. Also, the modification of the Si morphology from micron needles to nanoparticles by the Sr addition enhanced both the strengths and electrical conductivity of the developed alloy.
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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".