Silicon segregation in aluminium casting alloy
Bibliographic record
Abstract
The objective of the present study was to find an explanation for the observation made by earlier researchers that the distribution of silicon across dendrite branches in an aluminium–silicon casting alloy is sometimes anomalous, in that the concentration gradient is in the opposite direction to that predicted by solidification theory. Small specimens of aluminium alloy A356 were solidified to give a similar dendritic microstructure. One specimen was quenched from a temperature just above the eutectic temperature, giving the silicon distribution expected from theory, while a second specimen was cooled more slowly to give the anomalous silicon distribution, suggesting that it is caused by something occurring in the solid state. It was noted that there is a rapid decrease in solubility of silicon in aluminium with decreasing temperature below the aluminium–silicon eutectic temperature, so that a substantial amount of silicon is expected to come out of solution at temperatures above 500°C on cooling. An estimate of the diffusion rate of silicon in aluminium showed that, for normal cooling rates, this can occur by diffusion of silicon to the interdendritic silicon particles formed during the final stages of freezing, thereby removing silicon directionally from the dendrite branches and producing the observed anomalous silicon distribution.
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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".