Columnar-to-equiaxed grain transition in powder bed fusion via mimicking casting solidification and promoting in situ recrystallization
Bibliographic record
Abstract
Columnar grain structure typically formed along the build direction in the electron beam-powder bed fusion (EB-PBF) technique leads to anisotropic physical and mechanical properties. In this study, casting solidification condition was mimicked, and in situ recrystallization was promoted in EB-PBF to facilitate columnar-to-equiaxed grain structure transition in Alloy 718. This is achieved via a unique linear melting strategy coupled with a specific selection of process parameters in EB-PBF. It was found that site-specific melting using line order number (LON) function affected the cooling rate and temperature gradient, which controlled grain morphology and texture. A high LON resulted in a large equiaxed grain zone with a random texture, whereas a fixed LON with a high areal energy density led to a strong texture. The main driving force in the formation of cracks and shrinkage defects during the transition was investigated. A high LON at a fixed areal energy density reduced the average total shrinkage defects and crack length. The hardness was decreased through the transition, which was linked to the reduction in the size of the γ″ precipitates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".