Review of Simplified Models for the Pitting Potential and the Critical Pitting Temperature, Taking into Account Recent Observations
Bibliographic record
Abstract
From the 1980s through the early 2000s, building on pioneering work by Galvele and others, we developed some simplified models for pitting corrosion using the artificial pit electrode (pencil electrode) as the main experimental tool. Some of the main conclusions of this research are listed below, using CPT to denote the critical pitting temperature – - The critical pit chemistry for simple stainless steels, at room temperature, is not lower than 60% of saturation in FeCl2, and may be considerably higher, as the artificial pit surface tends to split into active and passive areas [1]. Very careful experimentation is required to detect this splitting phenomenon, and to reject conclusions that do not take it into account. - The variation of the pitting potential with log [Cl-], as discussed by Galvele, can be rationalized rather exactly by plotting a quantity called the transition potential (ET) against log [Cl-]. One can dial-in a limiting current density (dependent on pit depth) to harmonize both potentials – pitting potential and transition potential [2]. A similar procedure works for alloying and (low) temperature effects. - The CPT is a kind of active-passive transition potential where (essentially) a developing pit repassivates, no matter how concentrated the local solution [3-5], but with many small complexities. - The complex morphology of real pits involves active-passive transitions within a developing 3D cavity, leading to lacy metal covers and other observations [6-8]. This topic has recently become quite fashionable after a period of some years. In this presentation, the original observations and simplified models will be reiterated and defended. References: G.T. Gaudet, W.T. Mo, J. Tilly, J.W. Tester, T.A. Hatton, H.S. Isaacs and R.C. Newman, Mass transfer and electrochemical kinetic interactions in localized pitting corrosion, AIChE Journal, 32, 949-958 (1986). N.J. Laycock and R.C. Newman, Localized dissolution kinetics, salt films and pitting potentials. Corros. Sci., 39, 1771-1790 (1997). N.J. Laycock, M.H. Moayed and R.C. Newman, Metastable pitting and the critical pitting temperature. J. Electrochem. Soc., 145, 2622-2628 (1998). M.H. Moayed and R.C. Newman, Analysis of current transients and morphology of metastable and stable pitting on stainless steel near the critical pitting temperature. Corros. Sci., 48, 1004-1018 (2006). M.H. Moayed and R.C. Newman, The relationship between pit chemistry and pit geometry near the critical pitting temperature. J. Electrochem. Soc., 153, B330-B336 (2006). P. Ernst and R.C. Newman, Pit growth studies in stainless steel foils - I Introduction and growth kinetics. Corros. Sci., 44, 927-941 (2002). P. Ernst and R.C. Newman, Pit growth studies in stainless steel foils - II Effect of temperature, chloride concentration and sulphate addition. Corros. Sci., 44, 943-954 (2002). N.J. Laycock and S.P. White, Computer simulation of single pit propagation in stainless steel under potentiostatic control, J. Electrochem. Soc., 148, B264–B275 (2001).
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".