Correlation between microstructure and mechanical properties in additively manufactured Inconel 718 superalloys with low and high electron beam currents
Bibliographic record
Abstract
This study explored the correlation between microstructure and mechanical properties in additively manufactured Inconel 718 superalloys with low and high electron beam (EB) currents. The relative densities of the as-built Inconel 718 superalloys with low EB currents ranged from 99.45 to 99.79 %, while the alloys with high EB currents demonstrated relatively high relative densities ranging from 99.82 to 99.96 %. The microstructures of the alloys with low EB currents had columnar grain microstructures with a strong <0 0 1> texture parallel to the built direction (BD). The high-angle grain boundary density of the alloys with low EB currents was lower than with high EB currents. In addition, the alloys contained fine γ″ precipitates with an average size of 32 nm. Although the fracture-initiating sites for the alloys consisted of defects, such as micro-cracks and gas-entrapped pores, the alloys with low EB currents demonstrated excellent tensile strength and good uniform elongation due to the single-crystal-like microstructures and fine γ″ precipitates. The γ″ precipitates easily grew in deep and narrow melt pools due to sufficient thermal transfer with increasing penetration depth. However, the growth of γ″ precipitates was limited in the shallow and wide melt pools, and the shallow and wide melt pools resulted in single-crystal-like microstructures and strong <0 0 1> textures parallel to the BD. Therefore, the morphology of the melt pool, determined by the EB current, played an important role in the single-crystalline microstructure and growth of the γ” precipitates.
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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 | 0.001 | 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 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".