Synergistic effects of solute and pressure on phase transformation in titanium alloys: A first-principles study
Bibliographic record
Abstract
The phase stability and transformation between hexagonal close-packed (hcp) α-phase and body-centered cubic (bcc) β-phase in titanium (Ti) alloys are critical to their mechanical properties and manufacturing processes for a wide range of engineering applications. However, many factors, both intrinsic and extrinsic (e.g., solute elements and external pressures, respectively), may govern their phase transformations dynamically, which is crucial to the design of new Ti alloys with desired properties. In this work, we study the effects of various solute elements and external hydrostatic pressures on the solid-state phase transformations in Ti alloys using density functional theory and nudged elastic band calculations. The results show that both alloying and applied pressure reduce transformation barriers, with Al and Mo being most effective under ambient conditions, while Nb, V, Zr, and Sn show enhanced transformation kinetics under stress. Solute-induced modifications to the local electronic structure and bonding environment, particularly under pressure, contribute to variations in phase stability. We identify a synergistic interaction between solute effects and external stress, facilitating phase transitions that are unachievable under static conditions. These findings provide atomistic insights into the coupled chemical-mechanical mechanisms underlying phase transformations in Ti alloys with improved phase stability and mechanical performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".