Microstructure evolution of Al-Si hypoeutectic alloys prepared by controlled diffusion solidification
Bibliographic record
Abstract
Abstract The possibility of changing the dendritic microstructure associated with the conventional casting processes of hypoeutectic Al-Si alloys to non-dendritic microstructure by using the controlled diffusion solidification process (CDS) has been investigated. The successful CDS process depends on mixing two precursor alloys heated at a superheat condition near their respective liquidus temperature. Experimental work and simulation work using Ansys software was carried out in the present study by employing Al-Si and Al-Cu systems. This study investigates the effect of the content of the two precursor alloys, the mass ratio changing from 2.6 to 8.3, and the superheat of the first precursor alloy on changing the microstructure. The experimental results show that the pure aluminum used as the first precursor alloy needs more undercooling and agitation during the mixing to form the non-dendritic microstructure compared with hypoeutectic Al-Si alloys. Further, mixing pure aluminum with hypereutectic alloy can change the microstructure of hypoeutectic alloys leading to extending the possibility to choose the second precursor alloy. The results also show that a higher mass ratio is preferred when mixing pure aluminum with hypoeutectic alloy. Furthermore, the microstructure of the alloy Al- 6.45Si- 4Cu- 0.5Mg- 0.66Fe- 0.66 wt%Zn was successfully changed via the CDS process by mixing Al- 7.75Si- 0.79Fe- 0.78Zn- 0.6 wt%Mg at 2°C superheat into Al-24 wt%Cu at around 5°C superheat. The simulation results show that lower air bubbles and better distribution of the two precursor alloys happen during the mixing step when using the Al-Cu system.
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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".