Ultra-high strength and thermally stable Al-Mg-Si-Cu conductors microalloyed with Sc and Zr: Balancing strength and electrical conductivity
Bibliographic record
Abstract
This study examines the effects of Sc and Zr microalloying on the strength, electrical conductivity (EC), and thermal stability of Al-Mg-Si-Cu alloys developed for high-temperature conductor applications. Two alloy compositions were investigated: Alloy A (Al-Mg-Si-Cu base alloy free of Sc or Zr) and Alloy B (with 0.07 wt% Sc and 0.086 wt% Zr). Both alloys were subjected to a tailored thermomechanical treatment involving pre-aging at 120 °C, post-aging at 140 °C and 160 °C, and over-aging at 300 °C for 5 h. Alloy B was further processed using solution treatments at 500 °C (BS500) and 530 °C (BS530). The BS530 condition, post-aged at 160 °C, achieved the highest tensile strength of 518 MPa but exhibited relatively low electrical conductivity (45.0 %IACS). The BS500, over-aged at 300 °C, exhibited the best overall thermal stability due to forming finer and thermally stable Al 3 (Sc,Zr) dispersoids, and reached the highest EC (54.1 %IACS) with reasonably high strength (290 MPa). This strength value greatly surpasses the IEC 62004 AT2 requirement of 225 MPa, although conductivity fell slightly below the target of 55 % IACS. In contrast, the base alloy (A) achieved a maximum EC of 55.1 %IACS but significantly lower strength and thermal-resistant performance. Overall, the Sc and Zr microalloying, combined with tailored thermomechanical processing, enabled balanced combinations of strength, EC, and long-term thermal resistance—supporting the design and processing of next-generation aluminum conductors for elevated-temperature applications.
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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".