Investigation on electrical conductivity and hardness of 6xxx aluminum conductor alloys with different Si levels
Bibliographic record
Abstract
The impact of Si levels on electrical conductivity (EC) and hardness in Al-Mg-Si 6xxx aluminum conductor alloys was studied at different aging times. Three experimental alloys with the Si levels of 0.4, 0.66, 0.89 wt.% containing a constant Mg content of 0.65 wt.%, designated as Si4, Si6, and Si9, were selected. It is found that the average peak hardness of Si4, Si6, and Si9 alloys were 114, 127 and 140 HV, respectively. The Si9 alloy with the highest Si level exhibited the highest peak hardness, which was consistent with the number density of strengthening precipitates. However, the EC of all studied alloys at peak aging was lower than the minimum required one (52.5 %IACS). The higher Si level in the alloy, the longer aging time required to enhance EC. The Si4, Si6, and Si9 alloys reached the minimum required EC after 3, 5 and 34 h aging time, of which the corresponding hardness was 103, 119 and 111 HV, respectively. Consequently, the Si6 alloy represented a better trade-off between EC and hardness among three studied alloys. The quantitative analyses of precipitates at peak aging and overaging states were carried out by a transmission electron microscope (TEM) investigation.
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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".