Effect of nickel on the mechanical properties of spray-formed Al-15Si-2Cu alloy at elevated temperatures
Bibliographic record
Abstract
In the present study, the effect of nickel (Ni) on the mechanical properties of spray-formed (SF) Al-15Si-2Cu alloy at different temperatures was examined and evaluated with that of the as-cast (AC) alloy. The microstructure of SF alloys revealed uniformly distributed spherical shaped primary silicon and eutectic silicon phases along with fine Ni and Cu intermetallic particles dispersed throughout the equiaxed Al matrix. The microstructure of AC alloys consisted of coarse primary Si, flake-type eutectic phase, Cu-rich intermetallics with a complex branched morphology and a network of short strips. The mechanical properties of the alloys were assessed at temperatures of 30°C, 100°C, 200°C and 300°C. The SF alloys exhibited higher hardness than AC alloys at all temperatures with a maximum increase of 74 % at 30°C. The hardness of alloys showed a decreasing trend with increasing temperature. The mechanical strength of SF alloys was higher than that of the AC alloys across the entire temperature range from 30°C to 300°C with a decrease in ultimate tensile strength (UTS) by 4–6 % at 250°C. The SF alloys demonstrated a significant increase in UTS (25 % at 30°C and 40 % at 300°C) compared to the AC alloys. The Al-15Si-2Cu-2Ni alloy showed highest increase (14.3–18.6 %) and Al-15Si-2Cu-6Ni alloy showed the lowest increase (10.5 % to 14 %) in percent elongation between 30°C and 300°C. • Spray forming refined the microstructure of Al-15Si-2Cu-xNi alloys. • Spray formed alloys exhibited 74 % higher hardness than as-cast alloys at 30 ο C. • Tensile strength of spray formed alloys is 40 % higher than as-cast alloys at 300 ο C. • Ni in spray formed alloy enhanced thermal stability of alloy at high temperature.
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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".