Constitutive analysis of stress–strain curves in dynamic softening of high Nb- and N-containing austenitic stainless-steel biomaterial
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Bibliographic record
Abstract
High N-containing austenitic stainless steels have long been used as materials in orthopedic implants. For almost three decades, research has shown that ASTM F-1586 steel is an alternative for orthopedic applications involving severe loads and long implant survival rates in the human body. However, several studies have detected impaired mechanical strength of prostheses during use as a result of manufacturing processes. In this research work, the dynamic softening of this material is characterized based on a constitutive analysis of the stress–strain curves under conditions resembling those of industrial manufacturing, obtained by continuous isothermal hot torsion tests at different temperatures (900ºC-1200 °C) and strain rates (0.01–10s−1). The results indicate that the hot deformation apparent activation energy (Qdef = 594 kJ/mol) is high compared to other types of 300 series stainless steel, as are the ratios between critical (σc), peak (σp), steady state (σss) and saturation (σsat) stresses: σo/σp = 0.69, σc/σp = 0.94, σss/σp = 0.68 and σsat/σp = 1.01. These high values suggest competition between the mechanisms of work hardening (WH), dynamic recovery (DRV) and dynamic recrystallization (DRX), with delay in the onset and progression of DRX kinetics, significantly affected by the moderate stacking fault energy (γsfe ∼ 68.7 mJ/m2), solute atoms (Nb,N) and by fine Z-phase precipitates (CrNbN) at the grain boundaries, which favor softening with intense DRV. Thus, as can be seen, the parameters of WH (h), DRV (r) and DRX (t0.5, n) determine the shape of the stress–strain curves.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.000 | 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