Solidification microstructure selection maps for laser powder bed fusion of multicomponent alloys
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Solidification Microstructure Selection (SMS) maps provide a simple yet effective approach to predict the non-equilibrium solidification microstructure and grain morphology during Additive Manufacturing. In this study, SMS maps have been created for the Inconel 625 (IN625) alloy processed by Laser Powder Bed Fusion (LPBF). Toward this end, theoretical solid growth models, a model of the Columnar to Equiaxed Transition (CET), interface response theory, thermal simulation results and computational thermodynamics are utilized. The predicted microstructures are compared both qualitatively and quantitatively to experimentally-obtained micrographs. The theoretical analysis was also compared to the earlier analytical calculation for Al-10Si-0.5Mg alloy to show how differences in thermophysical properties affect the microstructural predictions. The theoretical predictions are shown to be in good agreement with the experimental results in terms of the resulting microstructure and dendrite arm spacings. A discussion on the use of SMS maps, formed over a broad range of thermophysical conditions, to help guide industry in improving LPBF microstructure, is provided.
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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) | 0.000 | 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