A scalable method for preparing Al–Mg–Si–Cu alloy profile with varies heterogeneous structures and their relationship with mechanical properties
Bibliographic record
Abstract
This work reports a simple method for manufacturing heterogeneous structured Al-Mg-Si-Cu alloy profile modified by TiB2-TiC particles using conventional hot extrusion and solution heat treatment. The heterogeneous structures containing different proportions of coarse grains and fine grains can be regulated by the solution treatment time, and their relationships with the mechanical properties are studied. The results show that the formation of the heterogeneous structure in the alloy is attributed to the non-uniform distribution of the TiB2-TiC particles, which have strong inhibition effects on the recrystallization in the particle-rich zone. When the proportion of coarse/fine grains in the heterostructure is about 2:1, the mechanical properties of the solution-treated alloy profile achieved a high level: tensile strength and yield strength are 345 MPa and 227 MPa, respectively, which are 35 % and 53 % higher than those of the as-extruded alloy with almost no loss of elongation. This work provides a strategy to advance the scalable manufacturing of heterogeneous structured Al alloy profile for various applications.
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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".