Solubility product of a Nb–N bearing austenitic stainless-steel biomaterial
Bibliographic record
Abstract
This research investigates the Z-Phase solubility product of austenitic stainless steel (ASS) ASTM F-1586 used as orthopedic implants under the solubilization procedure. Precipitate extraction by an electrolytic separation technique and analytical thermodynamic calculations as a function of the solubilization temperature and chemical composition were employed. In the first procedure of preferential electrolytic phase dissolution, samples were submitted to a solubilization treatment, followed by quenching. The specimens were subjected to a surface treatment then dissolved in solution. Following the dissolution, the electrolyte was vacuum filtered on a 0.20 μm polyvinylidene difluoride (PVDF) membrane and vacuum dried for 24 h. The microstructures were characterized via scanning electron microscopy (SEM/EDS) and transmission electron microscopy (TEM/EDX) techniques. The results revealed by the Z-phase (Cr2Nb2N2) precipitation potential (Ks) that the precipitates acted as a softening inhibitor agent and retarded the grain growth at lower solubilization temperature conditions (Ts < 1100 °C). The considerable amount of fine precipitates were mainly formed due to the nucleation and coalescence of Cr/NbN in the matrix. On the other hand, larger precipitates nucleated and coalesced above 1200 °C, and had their volume fraction reduced at this condition.
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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".