A mechanistic study of iron passivation and transpassive behavior in sulfate solutions using thermo-kinetic diagrams
Bibliographic record
Abstract
Understanding the dissolution and passivation of iron in aqueous environments is essential for enhancing its corrosion resistance and expanding its applications. We present Thermo-Kinetic (TK) diagrams for iron in deaerated solutions with no added sodium sulfate (Na2SO4) and with 0.1 M Na2SO4 over the pH range 1–14, constructed by integrating current density contours from potentiodynamic polarization with thermodynamic E-pH diagrams. TK diagrams indicate that in solutions with no added Na2SO4, iron passivates above pH 7, with a minimum passive current density (ip) of 5 ×10−6 mA·cm−2 at pH 8. The addition of 0.1 M Na2SO4 delayed passivation until pH 12 and increased ip nearly tenfold. Galvanostatic (GS) polarization and EIS validated the TK diagram results. XPS after GS polarization revealed an FeOOH/Fe2O3 film at pH 10, while Fe3O4/Fe2O3 dominated at pH 12 and 14. These results clarify how sulfate compromises iron passivity and highlight TK diagrams as a powerful tool for mapping corrosion behavior.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".