Embrittlement after high-temperature exposure to air of a near-γ TiAl alloy
Bibliographic record
Abstract
The loss of ductility of a Ti–48Al–2Cr–2Nb (at%) near-γ alloy after exposure to 80 % Ar–20 % O 2 at 700 °C for 1 h and 100 h has been investigated. In addition to marked decreases in ductility classically reported, increases in yield stress reaching +25 % have been observed. SIMS depth profiles enabled the determination of the 18 O isotope penetration depth via volume diffusion, which reached about 10 μm after 100 h of exposure. Site-specific lift–out by FIB, along with EBSD and TEM characterizations, were employed to examine the local transformations occurring in the diffusion zone and within the volume of exposed tensile specimens. In-situ TEM straining experiments were carried out on exposed and un-exposed specimens to study the influence of exposure on the microscopic mechanisms occurring in the bulk material. Results revealed the formation of chromium-rich precipitates and a recrystallized zone extending up to a depth of 15 μm from the surface after exposure. The dislocations in the subsurface layer were non-linear, likely due interactions between dislocation lines and oxygen solutes from the exposure atmosphere which potentially contribute to strengthening of the subsurface layer and ultimately to premature failure in this region. The elevated scattering in the in-situ TEM data did not allow to correlate the dislocation jump distances to the increase in yield stress.
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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".