Grain structure development and eutectic solidification of discontinuous magnesium borate whisker reinforced AA2024 matrix composite
Bibliographic record
Abstract
In the present research, the solidification behaviour of MBO whisker reinforced 2024 aluminium alloy matrix composite (MBO/AA2024) was studied by employing computer based thermal analysis, scanning electron microscopy and differential scanning calorimetry. The results show that the addition of MBO whiskers refines the grain structure in the matrix of the MBO/AA2024 composite. The nucleation of primary α-Al phase took place away from the whisker surfaces and started within the interstice of whiskers. The whiskers had almost no significant influence on the refinement of the eutectic phases.Dans cette recherche, on a étudié le comportement de solidification du composite (MBO/AA2024) à matrice d’alliage d’aluminium 2024 renforcée par des barbes de MBO, au moyen de l’analyse thermique automatisée, de la microscopie électronique à balayage et de l’analyse calorimétrique à compensation de puissance. Les résultats montrent que l’addition de barbes de MBO affine la structure de grain dans la matrice du composite MBO/AA2024. La nucléation de la phase primaire α-A1 prenait place à l’écart des surfaces de la barbe et commençait à l’intérieur de l’interstice des barbes. Les barbes n’avaient presque pas d’influence sur l’affinement des phases de l’eutectique.
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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".