Combined thermal, microstructural andmicrochemical analysis of solidificationof Al25Si3Cu alloy
Bibliographic record
Abstract
Purpose: This paper present thermal and microstructural and microchemical analyses were conducted on the unmodified experimental alloy Al20Si3Cu (B390.1) solidified in the High Temperature Universal Metallurgical Simulator and Analyser (HT UMSA) under atmospheric pressure (0.1 MPa) and a relatively low solidification rate (-1.2 K/s just after end of solidification), for identification of the thermal events during solidification and the phases in the as-cast structure. Design/methodology/approach: The HT UMSA platform, using a low thermal mass stainless steel cup, enabled the acquisition of high resolution thermal analysis data. Design/methodology/approach: A new approach for de-convolution of the first derivative thermal curves allowed detailed thermal and microstructural phase histories to be documented for solidification of Al-Si alloys. Recently developed SEM/EDS methodology allowed to determine composition and distribution of individual phases that are smaller than the X–ray volume. Findings: Simultaneous consideration of thermal microstructural and microchemical information allowed detailed understanding of the series of events that take place during solidification of Al casting alloy with complex chemistry. In our hypereutectic alloy we document growth of Al(1) dendrites and formation of secondary Si(2) and Al(2) phases all at temperatures higher than the binary equilibrium Al-Si eutectic temperature of 850 K. Practical implications: Even at this slow solidification rate detailed understanding of the solidification microstructure requires consideration of non-equilibrium processes during solidification. Originality/value: We propose an original set of hypotheses that consistently explain the observed non-equilibrium solidification behaviour. Proof of these hypotheses is beyond the scope of this work.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".