Effect of laser powder bed fusion process parameters on microstructure and coefficient of thermal expansion of Al6061
Bibliographic record
Abstract
High-performance aluminum (Al) alloys, including the 6xxx and 7xxx series, are considered promising materials for energy, aerospace, automotive, and defense applications. In this work, the laser powder bed fusion (L-PBF) technique was employed to fabricate Al6061. An optimized processing window for L-PBF was established to fabricate Al6061 with relative densities exceeding 99%, using a laser power range of 200-250 W, a scanning speed of 1000 mm/s, and a hatch spacing of 140 µm. This process resulted in complete melting within the energy density range of 44-50 J/mm3. Additionally, thermal expansion and average linear coefficient of thermal expansion (CTE) analyses revealed that parts produced at energy densities below 44.64-50 J/mm3 exhibited lower CTE, likely due to void formation in the lack of fusion mode. Similarly, higher energy densities (69.44 and 104.16 J/mm3) also caused a decrease in CTE, attributed to phase transformations and keyhole formation.
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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) | 0.002 | 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".