Influence of molybdenum additions on the microstructural properties of medium-Mn steels
Bibliographic record
Abstract
In this work, the impact of microalloying with molybdenum, ranging from 0.05 to 0.25 wt%, on the microstructural properties of as-cast medium manganese steel was explored. Four medium manganese steels with different molybdenum contents were designed using a CALPHAD approach. A duplex phase microstructure consisting of martensite and retained austenite was observed in all the steels investigated. Increasing Mo content delays the martensitic transformation and promotes the formation of equiaxed prior austenite grains, effectively suppressing γ-lean band formation observed in low-Mo alloys. The prior austenite grain refinement also offers additional nucleation pathways for solid-state martensitic transformation and reduces the preferential <100> casting texture. Mo addition therefore mitigates the effects of directional solidification and leads to a more uniform distribution of retained austenite throughout the microstructure. The element distribution in the constituent phases was investigated in detail. Mn, Mo and Si segregation to austenite was observed. The origins of elemental banding in medium manganese steels were also analyzed. The findings also revealed that increasing the molybdenum content led to an increase in the hardness of the steel.
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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".