Twinning Induced Plasticity and Work Hardening Behavior of Aged Cu–Ni–Si Alloy
Bibliographic record
Abstract
The work hardening behavior and deformed microstructure of the Cu–Ni–Si alloy aged at 723 K for various times and then deformed at 293 and 77 K were extensively investigated. The precipitate microstructure was also observed using transmission electron microscopy after aging treatment at 723 K for 0.30, 3.6, 64.8 and 345.6 ks. Deformation twins were clearly observed by transmission electron microscopy in the under-aged specimen deformed by 10% in tension at 293 K, in accordance with the enhanced work hardening rate observed during tensile deformation. The thickness of the deformation twins observed was approximately 1–40 nm. In addition, a significant fraction of larger deformation twins were observed by EBSD on the surface of the under-aged and peak-aged specimens tested at 77 K, for which the stress–strain behavior exhibited a nearly constant work hardening rate, i.e., high tensile strength and high elongation. These results show that the deformation twins formed during tensile deformation at 293 K contribute to strengthening of the specimen as new obstacles to the dislocation slip. Moreover, the enhanced twinning deformation at 77 K achieves high strength and elongation in the under-aged and peak-aged conditions. On the other hand, only a few deformation twins were observed in the supersaturated solid solution and over-aged specimens.
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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".