Effect of building direction on the microstructure and tensile properties of Ti-48Al-2Cr-2Nb alloy additively manufactured by electron beam melting
Bibliographic record
Abstract
This paper clarified a novel strategy to improve the tensile properties of the Ti-48Al-2Cr-2Nb alloys fabricated by electron beam melting (EBM), via the finding of the development of unique layered microstructure composed of duplex-like fine grains layers and coarser γ grains layers. It was clarified that the mechanical properties of the alloy fabricated by EBM can be controlled by varying an angle θ between EBM-building directions and stress loading direction. At room temperature, the yield strength exhibits high values more than 550 MPa at all the loading orientations investigated (θ = 0, 45 and 90°). In addition, the elongation at θ = 45° was surprisingly larger than 2%, owing to the development of this unique layered microstructure. The anisotropy of the yield strength decreased with increasing temperature. All the examined alloys exhibited a brittle-ductile transition temperature of approximately 750 °C and the yield strength and tensile elongation at 800 °C were over 350 MPa and 40%, respectively. By the detailed observation of the microstructure, the formation mechanism of the unique layered microstructure was found to be closely related to the repeated local heat treatment effect during the EBM process, and thus its control is further possible by the tuning-up of the process parameters. The results demonstrate that the EBM process enables not only the fabrication of TiAl products with complex shape but also the control of the tensile properties associated with the peculiar microstructure formed during the process.
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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".