Enhanced strength-ductility synergy in AA5052 alloy through nano/ultrafine structure induced by asymmetric reverse rolling (ARR)
Bibliographic record
Abstract
This study investigates the influence of asymmetric reverse rolling (ARR) strain on the microstructure, texture evolution, and mechanical properties of AA5052 aluminum alloy. Microstructural analysis revealed that deformation bands formed in α-aluminum grains at 50% ARR strain but disappeared upon further straining to 70%. Dynamic recovery (DRV) and grain subdivision commenced only after 30% ARR, facilitated by strain path changes induced by interpass sheet rotation. Intermetallic particles acted as nucleation sites for subgrains and recrystallized grains via particle-stimulated nucleation (PSN). At 70% ARR, continuous dynamic recrystallization (CDRX) generated a high density of nanoscale (20-100 nm) and ultrafine (100-500 nm) grains, attributed to strain-induced subgrain rotation. Texture analysis demonstrated intensified α-fiber orientation, with maxima of 3.1 and 3.6 multiples of random distribution at 50% and 70% ARR, respectively, linked to CDRX-driven texture sharpening. As the ARR strain increased, the difference between the hardness in the regions near the surface and the midthickness increased, creating a gradient in hardness after 70% deformation. Strength enhancement at low strains (<50%) correlated with dislocation accumulation and subgrain formation, while grain refinement dominated at 70% ARR. Strain hardening rate transitions aligned with a strengthening mechanism shift from dislocation-based to grain boundary-mediated effects. Fractography indicated retained ductile failure modes despite increased surface flatness at higher strains, consistent with strain localization in refined microstructures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".