Kinetics of Passive Film Growth on 304 Stainless Steel in H2SO4 Pickling Solution under Chemical Oxidation
Bibliographic record
Abstract
H2SO4-H2O2 mixtures are a promising and environmentally friendly passivation medium for the stainless-steel pickling process. The corrosion behavior of stainless steel is highly dependent on the kinetics of passive film growth. Long-term electrochemical measurements, including polarization resistance, open circuit potential (OCP), and electrochemical impedance spectroscopy (EIS) measurements were performed to investigate the evolution of the passive state of 304 stainless steel. According to the OCP results, an active-passive transition takes place in 10 ks in 0.5 M H2SO4 solution containing 0.005 M to 0.3 M H2O2. Polarization resistance results indicate that the passive film thickness keeps growing after OCP stabilization in the presence of H2O2. Electrochemical impedance spectroscopy (EIS) results confirmed that the growth of the passive film in H2SO4-H2O2 solutions takes about 9 h. Additionally, according to the Point Defect Model (PDM) and Mott–Schottky analysis, the semiconductor properties of the passive film on 304 stainless steel in H2SO4-H2O2 solution were studied. The results indicate that the passive film is an n-type semiconductor. The donor density is in the range of 1.6 × 10−21 cm−3 to 24 and decreases exponentially with increasing film formation potential (this potential coincides with the final OCP in the corresponding H2SO4-H2O2 solutions). By postulating that most donors are oxygen vacancies, the point defect properties including diffusivity and electrical field strength are obtained.
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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) | 0.001 | 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".