Microstructure tailoring of laser powder bed fused 316L impellers for enhanced mechanical properties and optimum electrochemical characteristics through hot isostatic pressing
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Bibliographic record
Abstract
This study investigates the design, manufacturing, and post-processing of 316L stainless steel impellers fabricated using laser powder bed fusion (LPBF) for optimum mechanical properties and corrosion resistance. The as-built components were fabricated using optimized manufacturing parameters, starting with reduced-dimension prototypes featuring various angles. Tailoring the characteristics of the impellers involved stress relieving, hot isostatic pressing (HIP) at 100 MPa and 1150 °C for 4 h, and machining. To assess the impact of these processes on the component functionality, microstructural, mechanical, and electrochemical (MMEC) characterizations were conducted. The as-built microstructure displayed hierarchical features, including melt pools, micrograins, and sub-grains. Following the HIP process, melt pool boundaries and sub-grain features disappeared, resulting in more equiaxed and finer grains and a reduction in porosity to 99.8 % ± 0.05. Additionally, the formation of annealing twins was observed post-HIP, influencing both mechanical and electrochemical properties. While the ultimate tensile strength decreased after HIP, the elongation to failure improved, and both ultimate tensile and yield strength met the standard requirements for 316L stainless steel. Electrochemical analysis showed similar corrosion behavior for both as-built and HIP components, though resistance to localized corrosion, particularly pitting, slightly decreased after HIP. However, HIP caused the least reduction in localized corrosion resistance when compared to other post-heat-treatment techniques observed in LPBF components. Overall, HIP proved to be an effective heat-treatment process for tailoring physical, mechanical, and electrochemical properties of impellers.
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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