Some Extensions of the Galvele Approach to Localized Corrosion, Including the Effect of Cation Complexation
Bibliographic record
Abstract
Analytical and numerical modeling have been used to extend the understanding of pitting corrosion in a one-dimensional geometry. The approach is based on that of Galvele [1] and later experimental studies that supported many of Galvele’s findings [2], but with more detail and new features. We have examined both ideal solutions, and non-ideal solutions where the diffusivity (D) is a function of concentration (c) for any species, as well as cation complexation by chloride. The essential result that Galvele obtained was: Epit = A – B log [NaCl], where Epit is the pitting potential and B should be 0.059 V at 298 K. Laycock and Newman [2] clarified that the quantity A contained the kinetics of the anodic dissolution reaction, and defined a quantity that they called the transition potential, ET, which is the potential where the anodic current density i becomes equal to the anodic limiting current density, iL. The origin of Galvele’s equation is an analytical solution of the governing reaction-transport equation (Nernst-Planck equation) considering an unreacting ion such as Cl-. In this solution, as refined by Newman [3], the second term in Galvele’s equation is the IR drop in the pit at the limiting current density iL. Importantly, iL depends on [NaCl] because the contribution of migration to the outward flux of dissolved metal cations increases as [NaCl] decreases. In the present work, we have examined the following refinements, with the following preliminary outcomes: The variation of B with [NaCl] – B is constant at 0.059 V over a certain range of [NaCl], but decreases at high [NaCl]. This is easily understood physically. At low [NaCl] there appear to be small deviations from 0.059 V that are still under investigation. The effect of introducing a D(c) – this turned out to be an intriguing area of study, and new results will be presented at the meeting. Briefly, the effect of varying diffusivity is not as great as might be assumed. Cation complexation – this is the latest aspect to be investigated. Changes in B with complexation are expected. Such changes may explain the different empirical values of B found in different materials including stainless steels. References: Jose R. Galvele, Transport Processes and the Mechanism of Pitting of Metals. J. Electrochem. Soc., 1976, 123(4), 464-474. N.J. Laycock, R.C. Newman, Localised Dissolution Kinetics, Salt Films and Pitting Potentials. Corrosion Science, 1997, 39(10-11), 1771-1790. R.C. Newman, Pitting Corrosion of Metals, The Electrochemical Society Interface, 2010, 19(1), 33-38.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".