Microstructure Characterization and Mechanical Properties of Al Alloyed 9Cr ODS Steels with Different Al Contents
Bibliographic record
Abstract
The microstructural evolution of different Al contained (0.4, 2.5, and 4.5 wt%) Fe–9wt%Cr ODS steels (hereinafter referred to as 0.4Al‐ODS, 2.5Al‐ODS, and 4.5Al‐ODS) is investigated using XRD and TEM. The XRD analysis shows that the addition of Al into the Fe–9wt%Cr ODS steels leads to the formation of substitutional solid solutions, and the interplanar spacing increases with the increase of Al content. According to TEM bright field image observation, the 0.4Al‐ODS steel shows ferrite/martensite duplex microstructure, while 2.5Al‐ODS and 4.5Al‐ODS steels show a single‐phase of ferrite, which is in agreement with the thermodynamic phase diagram calculation. The dispersed particles is mainly Y–Al–O oxide according to EDS analysis, and the Y/Al ratio of most of dispersed particles is less than 1 in all Al alloyed ODS steels. The dislocation density of the three steels is calculated by the residual strain of XRD. The results show that, compared to 2.5Al‐ODS and 4.5Al‐ODS steels, the 0.4Al‐ODS steel contains more dislocations. The strengthening mechanism analysis shows that the modified theoretical hardening models fit well with experimental data of yield strength for 2.5Al‐ODS and 4.5Al‐ODS steels.
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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 | 0.001 | 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) | 0.001 | 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".