Softening Mechanisms of the AISI 410 Martensitic Stainless Steel Under Hot Torsion Simulation
Bibliographic record
Abstract
This study investigated the softening mechanisms of the AISI 410 martensitic stainless steel during torsion simulation under isothermal continuous in the temperature range of 900 to 1150 °C and strain rates of 0.1 to 5.0s-1. In the first part of the curves, before the peak, the results show that the critical (εc) and peak (εp) strains are elevated for higher strain rate and lower temperatures contributing for higher strain hardening rate (h). Moreover, this indicated that dynamic recrystallization (DRX) and dynamic recovery (DRV) are not effective in this region. After the peak, the reductions in stresses are associated to the different DRX/DRV competitions. For lower temperatures and higher strain rates there is a delay in the DRX while the DRV is acting predominantly (with low Avrami exponent (n) and high t0.5). The steady state was reached after large strains showing DRX grains, formation of retained austenite and the presence of chromium carbide (Cr23C6) and ferrite δ at the martensitic grain boundaries. These contribute for impairing the toughness and ductility on the material. The constitutive equations at the peak strain indicated changes in the deformation mechanism, with variable strain rate sensitivity (m), which affected the final microstructure.
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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) | 0.003 | 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".