Laser-Based Additive Manufacturing Processability and Mechanical Properties of Al-Cu 224 Alloys with TiB Grain Refiner Additions
Bibliographic record
Abstract
This study investigated the impact of TiB grain refiner additions on the microstructural evolution, hot tearing susceptibility, and mechanical properties of Al-Cu 224 alloys to enhance their processing performance during the selective laser melting (SLM) process. A simple laser surface remelting method was utilized to simulate laser-based rapid solidification. The results revealed that the addition of appropriate amounts of TiB grain refiner could completely eliminate the solidification cracks during the laser surface remelting process. The introduction of TiB2 particles in the melt pools through the TiB grain refiner addition changed the grain morphology from a coarse columnar to a fine equiaxed structure, and the grain sizes were reduced from 13 to 15 μm in the base alloys to 5.5 μm and 3.2 μm in the alloys with 0.34 wt% Ti (B-3TiB) and 0.65 wt% Ti (ZV-6TiB) additions, respectively. The hardness values of the modified B-3TiB and ZV-6TiB alloys reached 117 and 130 HV after a T6 heat treatment, which surpassed the hardness of conventional AlSi10Mg alloys by at least 15–30%. This improvement was attributed to the finer grains and nanoscale θ′/θ″ precipitates. The results demonstrate that the TiB grain refiner addition can significantly improve the processability and mechanical properties of Al-Cu 224 alloys for SLM applications, offering a promising solution to the challenge of high hot tearing susceptibility in high-strength aluminum alloys.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".