Precipitation of iron-rich intermetallics and mechanical properties of Al–Si–Mg–Fe alloys with Al–5Ti–B
Bibliographic record
Abstract
Effects of added Al–5Ti–B master alloys on precipitation of iron-rich intermetallics and mechanical properties of A356 cast alloys with high Fe content (1.5 wt-%) were investigated using image analysis, scanning electron microscopy, and tensile testing. Results show that added Al–5Ti–B has apparent refinement on α (Al) grain size of A356 alloys that have high Fe content. 12 wt-% Al–5Ti–B is beneficial for improving mechanical properties of A356 cast alloys with high Fe content. Improved mechanical properties can be attributed to refined microstructure, the proper amounts of TiB 2 and Ti(AlSi) 3 , and decreased porosity. An excessive amount of Al–5Ti–B deteriorates mechanical properties of alloys because it leads to the formation of large secondary intermetallics and increased porosity.
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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".