On the intermetallic constituents in the sodium-induced edge cracking of hot-rolled AA5182 aluminum alloys
Bibliographic record
Abstract
The productivity and recovery of hot-rolled Al-Mg-Mn sheets often suffer from sodium-induced edge cracking. In this study, AA5182 ingots with different levels of Na were prepared by direct-chill (DC) casting, and were then subsequently subjected to homogenisation and hot-rolling processes. The edge crack occurrence during hot rolling in the pass #11 (84% reduction) and pass #18 (96% reduction) was investigated, with special attention paid to the impact of intermetallic constituents in the ingot subsurface region, where all edge cracks were initiated. Correlations between the susceptibility to edge cracking, enriched intermetallic constituents in the inverse segregation zone, Mg2Si cavitation, meniscus bands, and Na contamination were observed. The results revealed that Fe-rich intermetallic particles were not involved in crack formation, while Mg2Si particles had a strong tendency to debond from the Al matrix and form cavities at the edges of the rolled strip. The higher the Na content, the more severe the Mg2Si cavitation, and consequently, the higher the susceptibility to edge cracking. Numerous debonded Mg2Si particles contaminated with Na in the subsurface region provided favourable conditions for crack initiation and propagation. The role of the meniscus bands on the large and profound edge cracks was also elaborated.
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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) | 0.000 | 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 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".