Grain Boundary and Microstructural Characterization of Heat-Treated As-Rolled 2205 Duplex Stainless Steel
Bibliographic record
Abstract
The detrimental precipitation at the 2205 duplex stainless steel (DSS) grain boundaries has characterized the material to have poor workability after being hot-rolled. However, the detrimental precipitation in the microstructure is largely influenced by the cooling rate or method. There is an insufficient investigation of this steel's grade interfaces and grain boundaries to rationale its poor workability. This study investigates the influence of heat treatment of hot-rolled 2205 DSS to eliminate the precipitation at the grain boundaries and a detailed microstructural study. The procedure was carried out by heat-treating the as-rolled 2205 DSS to achieve the equiaxed and Widmanstätten austenite morphologies. The characterization was conducted using an optical microscope, electron backscatter diffraction and X-ray diffraction. It was found that the Widmanstätten morphology carried a high fraction of austenite-ferrite interfaces and high grain boundary responsible for the steel cracking during hot rolling. The SEM analysis observed an incoherent interface in Widmanstätten morphology, while the equiaxed demonstrated a coherent interface. XRD detailed new phases such as martensite and cementite in Widmanstätten and equiaxed morphologies, respectively. The Widmanstätten will quickly be susceptible to crack initiation under the application.
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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".