Effects of Ni Content and Alloying Elements on Electrical Conductivity, Mechanical Properties, and Hot Tearing Susceptibility of Al-Ni-Based Alloys
Bibliographic record
Abstract
The Aluminum-Nickel alloy system exhibits good potential for rotor applications in electric vehicles, which require good castability, high electrical conductivity (EC), and mechanical strength. In the present study, the microstructure, hot tearing susceptibility (HTS), electrical conductivity, and mechanical properties of binary Al-xNi (x: 1 to 5% wt%) alloys were investigated. The results showed that the Al-1Ni alloy exhibited the highest EC of 57.6% IACS. However, increasing the Ni content to 5% led to a decrease in EC and a significant reduction in HTS. In addition, increasing the Ni content from 1 to 5% slightly enhanced the yield strength from 70.4 to 83.2 MPa showing a weak strengthening effect. The effect of Si and Mg addition on the strength and EC of Al-1Ni alloy was studied. By adding 0.6% Si and 0.6% Mg to the Al-1Ni alloy, the yield strength was enhanced to 156.6 MPa after T5 and 287.5 MPa after T6, respectively, while maintaining a high EC (51% IACS). The significant improvement in yield strength was attributed to the presence of nanosized MgSi precipitates as the strengthening phase, which was confirmed by TEM analysis.
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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".