Influence of heating and cooling routes on the isothermal β → ω transition in Ti–22Nb–6Zr alloy
Bibliographic record
Abstract
The influence of heating and cooling routes prior to the Ti–22Nb–6Zr (at.%) shape memory alloy ageing on the intensity of the isothermal ω iso phase formation in the temperature range from 250 to 350 °C for 1 and 3 h was studied by X -ray diffraction. It was shown that for intensive ω iso phase formation, the most efficient scheme for entering the ageing interval includes rapid water cooling to the room temperature from the annealing temperature of 600 °C and subsequent rapid heating to the ageing temperature of 300 °C. All other schemes used for entering the aging interval including slow cooling and/or heating do not lead to the formation of any X -ray identifiable ω iso phase amount. Whereas, the β → ω iso transition in the temperature range from 250 to 350 °C has a pronounced C-shaped kinetics with a maximum at 300 °C. When aged in the entire range of t = 250÷350 °С, the alloy features higher durability and hardness compared to the initial state. Moreover, the hardness gradually increases with an increase in the ageing temperature from 250 to 300 °C and remains constant in the temperature range of t = 300÷350 °С. The β phase lattice parameter of the Ti–22Nb–6Zr alloy remains unchanged over the entire aging temperature range of 250–350 °C, which indicates the absence of noticeable diffusion element redistribution in the solid solution during the ω iso phase formation. The ω iso phase formed during the Ti–22Nb–6Zr alloy ageing over the entire temperature range of t = 250÷350 °С has the ratio с ω / а ω = 0.613 ± 0.002, which is similar to the с ω / а ω ratio for the shear-type athermal ω ath phase, which in turn further emphasizes the identity of these two phase varieties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".