Influence of cooling rate and composition on formation of intermetallic phases in solidifying Al–Fe–Si melts
Bibliographic record
Abstract
Aluminium alloys containing 0·3%Fe and 0·05%Si, 0·3%Fe and 0·15%Si, 0·3%Fe and 0·45%Si, and 0·5%Fe and 0·2%Si were solidified with different cooling rates. Shapes of intermetallic particles and their spatial distribution in the alloys were characterised by optical and scanning electron microscopy. X-ray diffraction analysis was used to establish the types of intermetallic phases extracted from the alloys by dissolving the FCC matrix in boiling phenol. The influence of melt superheating on the microstructure was analysed by comparing phase portraits of alloys solidified from melts whose temperatures before casting were 100 and 350°C above the liquidus.On a solidifié des alliages d’aluminium contenant 0·3%Fe et 0·05%Si, 0·3%Fe et 0·15%Si, 0·3%Fe et 0·45%Si et 0·5%Fe et 0·2%Si, à différentes vitesses de refroidissement. On a caractérisé la forme des particules intermétalliques et leur distribution spatiale dans les alliages, au moyen de la microscopie optique et de la microscopie électronique à balayage. On a utilisé l’analyse de la diffraction des rayons X pour établir les types de phases intermétalliques extraites des alliages par dissolution de la matrice FCC dans du phénol en ébullition. On a analysé l’influence de la surchauffe du bain sur la microstructure en comparant les images de phase des alliages solidifiés à partir des bains dont les températures avant le moulage étaient de 100 et de 350°C au-dessus du liquidus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".