Strengthening mechanisms in vanadium-microalloyed medium-Mn steels
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this work, the impact of adding vanadium, ranging from 0 to 2 wt%, on the microstructure and mechanical properties of as-cast medium manganese steel was explored. A dual phase microstructure consisting of martensite and retained austenite was observed in the 0 V, 0.05 V and 0.8 V conditions. The 2 V condition contained retained austenite, lath martensite, and δ-ferrite bands. The retained austenite fraction and prior austenite grain size initially increased at lean vanadium concentrations but significantly dropped at the highest vanadium concentration. The element distribution in the constituent phases was investigated in detail. Mn, C and Si partitioning to austenite was observed in the 0 V, 0.05 V and 0.8 V conditions. V and C segregation to the grain boundaries and significant grain refinement were evident in the 2 V condition. The findings also revealed that increasing the vanadium content led to an increase in the hardness of the steel. This assessment was validated by tensile testing, which showed an improvement in yield and tensile strength of the steel with increasing vanadium content, and were supported by reconstruction of the parent austenite grains employing martensitic structures. Finally, the influence of different strengthening mechanisms on the yield strength of as-cast, microalloyed medium-manganese steels was also discussed in terms of simulated stacking fault energy, as well as the quantitative contributions from solid solution, grain boundary, and precipitation strengthening mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it