Effects of Post-Sinter Processing on an Al–Zn–Mg–Cu Powder Metallurgy Alloy
Bibliographic record
Abstract
The objective of this work was to study the effects of several post-sinter processing operations (heat-treatment, sizing, shot peening) on a press-and-sinter 7xxx series aluminum powder metallurgy (PM) alloy. The characterization of the products was completed through a combination of non-contact surface profiling, hardness measurements, differential scanning calorimetry (DSC), transmission electron microscopy (TEM), X-ray diffraction (XRD), tensile, and three-point bend fatigue testing. It was determined that sizing in the as-quenched state imparted appreciable reductions in surface hardness (78 HRB) and fatigue strength (168 MPa) relative to counterpart specimens that were sized prior to solutionizing (85 HRB and 228 MPa). These declines in performance were ascribed to the annihilation of quenched in vacancies that subsequently altered the nature of precipitates within the finished product. The system responded well to shot peening, as this process increased fatigue strength to 294 MPa. However, thermal exposure at 353 K (80 °C) and 433 K (160 °C) then reduced fatigue performance to 260 MPa and 173 MPa, respectively, as a result of residual stress relaxation and in-situ over-aging.
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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".