Cyclic Deformation of Ultra-Fine Grained Commercial Purity Aluminum Processed by Accumulative Roll-Bonding
Bibliographic record
Abstract
Accumulative Roll-Bonding (ARB) is one of the more recently developed techniques capable of producing bulk ultra-fine grained (ufg) metals. There are still many aspects of the behavior of ufg metals that lacks an in-depth understanding, such as a generalized view of the factors that govern the cyclic deformation mechanism(s). This study aims to advance the understanding of the cyclic deformation behavior of ufg metals through the systematic investigation of ARB processed aluminum upon cyclic loading. It was found that the cyclic softening response often reported for ufg metals is largely influenced by the microstructure stability as the cyclic softening response is facilitated by grain coarsening which becomes inhibited with highly stable microstructure. On one hand, shear bands resembling braids of dislocations trespassing multiple grains have been observed to operate for the accommodation of the imposed cyclic strain in cases where grain coarsening is largely restricted. On the other hand, it was found that the microstructure stability can be overcome at higher applied cyclic plastic strain levels, leading to grain coarsening and thus a cyclic softening response. The findings in this study have further confirmed that the cyclic softening behavior found in many ufg metals, which may be detrimental in practical applications, can be inhibited by improvements in the microstructure stability.
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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) | 0.002 | 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".