The Effects of Heat Treatments and Tungsten Additions on Microstructures and Tensile Properties of Powder Metallurgy Ti-48Al-2Nb-2Cr
Bibliographic record
Abstract
The microstructures and tensile properties of a fully lamellar Ti-48Al-2Cr-2Nb, and two tungsten-modified versions, Ti-48Al-2Cr-2Nb-0.5W and Ti-48Al-2Cr-2Nb-1.0W (atomic percent) are investigated. Gas atomized powders are consolidated by hot isostatic pressing followed by solution treatment and aging. The microstructures are characterized by optical, scanning electron, and transmission electron microscopy and mechanical properties are characterized by room temperature tensile testing. The solution heat treatment, combined with controlled cooling, generates relatively fine, fully lamellar grains. Tungsten reduces the propensity for martensitic gamma formation during cooling, and slows down lamellar coarsening as well as the formation of equiaxed gamma phase during aging. The aging treatment stabilizes the microstructure and, in the tungsten-modified alloys, causes beta phase precipitation at lamellar interfaces and grain boundaries. Both aging and tungsten additions increase the alloy strength and reduce ductility. The fracture morphologies of the alloys are similar and exhibit mixed-mode fracture consisting of inter- and intra-granular cracking, as well as inter-lamellar cracking.
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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 | 0.001 |
| 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".