A mechanistic model for oxide growth and dissolution during corrosion of Cr-containing alloys
Bibliographic record
Abstract
We have developed a corrosion model that can predict metal oxide growth and dissolution rates as a function of time for a range of solution conditions. Our model considers electrochemical reactions at the metal/oxide and oxide/solution interfaces, and the metal cation flux from the metal to the solution phase through a growing oxide layer, and formulates the key processes using classical chemical reaction rate or flux equations. The model imposes mass and charge balance and hence, is labeled as the Mass Charge Balance (MCB) model. Mass and charge balance dictate that at any given time the oxidation (or metal cation) flux must be equal to the sum of the oxide growth flux and the dissolution flux. For each redox reaction leading to the formation of a specific oxide, the metal oxidation flux is formulated using a modified Butler-Volmer equation with an oxide-thickness-dependent effective overpotential. The oxide growth and dissolution fluxes have a first-order dependence on the metal cation flux. The rate constant for oxide formation also follows an Arrhenius dependence on the potential drop across the oxide layer and hence decreases exponentially with oxide thickness. This model is able to predict the time-dependent potentiostatic corrosion behaviour of both pure iron, and Co-Cr and Fe-Ni-Cr alloys.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".