From high cooling rates to high creep performance: Role of metastable beta in in-situ alloyed Ti64-TiAl alloys fabricated by laser powder bed fusion
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Bibliographic record
Abstract
This study employs a novel processing approach using laser powder bed fusion (L-PBF). It leverages rapid cooling to develop a metastable microstructure that can retain or revert to suit both room and high-temperature applications. This approach is paired with a cost-effective blending strategy to fabricate novel alloys with microstructures that integrate ductile and hard phases. The study demonstrates the effectiveness of this approach in significantly enhancing the creep performance of Ti-6Al-4V (wt. %) through in situ alloying with Ti-48Al-2Cr-2Nb (at. %) at weight fractions of 20% and 40% via L-PBF. A tailored microstructure was achieved, leading to crack free samples. X-ray diffraction (XRD) phase analysis identified a metastable microstructure comprising the ductile β phase alongside hard α/α′/α 2 phases. A significant presence of β phases was observed in the 40% TiAl alloy, comprising 80% of the scanned area according to electron backscatter diffraction (EBSD) analysis, demonstrating the influence of rapid cooling in retaining high-temperature phases. Results from transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and selected area electron diffraction (SAED) indicated a high dislocation density within the α phase, which contributed to crack nucleation during mechanical testing. The heat-treated alloys, in which the β phase revert to α 2 , exhibited creep lifetime that surpassed Ti64 by 380% for the 20% TiAl alloy and over 600% for the 40% TiAl alloy. The combination of β and α phases at room temperature contributed to a yield strength of 966 MPa for 20% TiAl and 741 MPa for 40% TiAl, along with elongation percentages of 6.8% for 20% TiAl and 3.2% for 40% TiAl, both of which surpassed those of TiAl. These results pave the way for processing other materials beyond these specific alloys, enabling a wide range of applications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it