Effect of Annealing Heat Treatment on the Microstructural Evolution and Mechanical Properties of Hot Isostatic Pressed 316L Stainless Steel Fabricated by Laser Powder Bed Fusion
Bibliographic record
Abstract
In this work, the microstructural features and mechanical properties of an additively manufactured 316L stainless steel have been determined. Three types of samples were characterized: (i) as printed (AP), (ii) annealing heat treated (AHT), and (iii) hot isostatic pressed and annealing heat treated (HIP + AHT). Microstructural analysis reveals that the AP sample formed melt pool boundaries with nano-scale cellular structures. These structures disappeared after annealing heat treatment and hot isostatic pressing. The AP and AHT samples have similar grain morphologies; however, the latter has a lower dislocation density and contains precipitates. Conversely, the HIP + AHT sample displays polygon-shaped grains with twin structures; a completely different morphology compared to the first two samples. Optical micrography reveals that the application of hot isostatic pressing reduces the porosity generated after laser processing. The tensile strengths of all the samples are comparable (about 600 MPa); however, the elongation of the HIP + AHT sample (48%) was superior to that of other two samples. The enhanced ductility of the HIP + AHT sample, however, resulted in lower yield strength. Based on these findings, annealing heat treatment after hot isostatic pressing was found to improve the ductility of as-printed 316L stainless steel by as much as 130%, without sacrificing tensile strength, but the sample may have a reduced (40%) yield strength. The tensile strength determined here has been shown to be higher than that of the hot isostatic pressed, additively manufactured 316L stainless steel available from the literature.
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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 | 0.000 |
| 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".