Remelting-based microstructure engineering in laser powder bed fusion: A case study in 316L stainless steel
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Bibliographic record
Abstract
In laser powder bed fusion (LPBF), the formation of bulky columnar grains often results in undesirable mechanical anisotropy. Here, we demonstrate a new strategy to control the microstructure in LPBF through tuning melt pool overlaps without changing energy densities and scan patterns. Using 316L stainless steel as an example, we generate a wide range of grain sizes and morphologies. The underlying mechanism is associated with the retainment or elimination of newly nucleated grains at a melt pool during the formation of subsequent melt pools. The propensity of retainment or elimination of grains is largely dependent on the extent of melt pool overlaps because the grains are prone to nucleate at the free-surfaces of melt pool boundaries. This facile strategy could be applicable to a wide range of metallic alloys, paving a new way for microstructure engineering in additive manufacturing.
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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 it