Investigation of the structure stability and superelastic behavior of thermomechanically treated Ti-Nb-Zr and Ti-Nb-Ta shape-memory alloys
Bibliographic record
Abstract
The superelastic parameters of Ti-Nb-Ta and Ti-Nb-Zr alloys, such as Young’s modulus, residual strain, and transformation yield stress after thermomechanical treatment (TMT), were determined during cyclic mechanical tests using the tension-unloading scheme (maximum strain 2% per cycle, ten cycles). The superelastic parameters and the alloy structure have been studied by electron microscopy and X-ray diffraction analysis before and after testing and after holding for 40 days, as well as after retesting. The Young’s modulus of the Ti-Nb-Ta alloy decreases from 30–40 to 20–25 GPa during mechanocycling after TMT by different modes; however, it returns to its original magnitude during subsequent holding for 40 days, and changes only a little during repeated mechanocycling. The Young’s modulus of the Ti-Nb-Zr alloy changes insignificantly during mechanocycling, recovers during holding, and behaves stably upon repeated mechanocycling. Surface tensile stresses arise during mechanocycling, which facilitate the development of martensitic transformation under load, orient it, and thereby promote a decrease in the transformation yield stress and the residual strain. The enhancement of the level of initial strengthening stabilizes the superelastic behavior during mechanocycling.
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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".