Influence of Nickel on High‐Temperature Oxidation and Characteristics of Oxide Layers in Two High‐Strength Steels
Bibliographic record
Abstract
The oxidation behaviors of two high‐strength medium carbon steels with different Ni concentrations are investigated by means of differential thermal analysis equipped with thermogravimetry (TG). Four different oxidation temperatures and five oxidation times are tested. A parabolic behavior is observed for the oxide growth in both alloys; however, the relative increases in the oxidation rate from one temperature to another are not similar for both alloys, and the oxidation kinetics of the Ni‐rich steel are significantly lower than those of the low Ni alloy. On the basis of the TG results, the activation energy for the oxidation of the two alloys is determined. The influence of Ni content on the microstructure and characteristics of the different oxide layers is studied using a combination of laser confocal microscopy, electron microscopy, and X‐ray diffraction (XRD) analysis. The results revealed a clear influence of Ni on the nature and relative presence of different oxide layers. The results are interpreted in terms of the influence of Ni on the diffusion of oxygen through the oxide layer.
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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 | 0.001 |
| 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) | 0.000 | 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 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".