Corrosion Behavior of Deep Cryogenically Treated AISI 420 and AISI 52100 Steel
Bibliographic record
Abstract
In this work, the impact of deep cryogenic and tempering treatment on the corrosion behavior of AISI 420 (UNS S42000) and AISI 52100 (UNS G52986) steel in 3.5% sodium chloride (NaCl) and sodium bicarbonate (NaHCO3) + 0.25% NaCl solution was studied using open-circuit potential (OCP), potentiodynamic polarization, and electrochemical impedance spectroscopy (EIS) measurements. The relationship of microstructure and the electrochemical response of differently treated samples was discussed. The results indicated that, compared with the conventional treatment, no significant modification of the electrochemical corrosion behavior after cryogenic treatments was observed. No passive behavior was observed for either AISI 420 or AISI 52100 in 3.5% NaCl, whereas it was observed in NaHCO3 + 0.25% NaCl solution. Different effects of tempering treatment on the corrosion behavior between AISI 420 and AISI 52100 were observed due to different modifications of the microstructure during the tempering process. The amount of retained austenite has a critical role in determining the pitting resistance. The pitting resistance increased with the amount of retained austenite.
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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".