Effect of Si, Mn, Be and Sr Addition on the Tensile Properties of 6061 Type Alloys: Role of Aging Treatment
Bibliographic record
Abstract
The present study was performed on a 6061-type alloy to examine the effects of minor additions (Si, Mn, Be, Sr) of the type of precipitated Fe-based intermetallics, in terms of Fe/Si ratios. All alloys were grain refined (0.15%Ti in the form of Al-5%Ti-1%B) to minimize hot tearing during casting. The effect of these intermetallics on the alloy tensile properties was also investigated. Tensile test bars were solutionized at 520 °C followed by quenching in warm water at 60 °C to avoid cracking. The quenched bars were aged at 175 °C for periods up to 100 h. Characterization of the formed intermetallics as well as phase precipitation were carried out using field emission scanning electron microscopy. In Be-treated alloys, α-Al8Fe2SiBe phase may precipitate along with α-Al15(Fe, Mn)3Si2 phase. In addition, Be results in fragmentation of the α-Fe phase when the alloy was Sr-modified, leading to better tensile properties, compared to those obtained from the base alloy under same conditions. It should be noted that this study does not promote the use of Be as it is a toxic element.
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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".