Microhardness of binary near-equiatomic Ti-Ni alloys after severe cold rolling and post-deformation annealing
Bibliographic record
Abstract
Comparative HV-microhardness and TEM studies of Ti-50.0at%Ni and 50.26at%Ni alloys subjected to cold-rolling (e=0.3, 1 and 1.72) and post-deformation annealing at 100-700C (1 hour) are presented. Based on the TEM-measured grain size data for Ti-50.0at%Ni alloy as a function of an annealing temperature (T PDA ) higher than 250 o C, it was possible to evaluate the grain size (d) of the near-equiatomic Ti-Ni alloys at T PDA <250 o C, using exponential extrapolation distribution of the d-T PDA data. It was shown that below a critical grain size (d c = 10 nm), the smaller the grain size (as a result of the decrease in annealing temperature), the lower the microhardness. This softening phenomena can be described, with good correlation between the approximation and experimental data, by the normal-abnormal Hall-Petch transition caused by the influence of the intercrystalline regions and by the melting temperature grain-size dependence.
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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".