Synergism of Electrochemical and Mechanical Factors in Erosion−Corrosion
Bibliographic record
Abstract
A theoretical model was developed on basis of nonequilibrium thermodynamics, dislocation kinetics, and electrochemistry, which may lead to the quantitative assessment of material loss produced by the synergism of mechanical and electrochemical factors in an erosion-corrosion process, As predicted by this model, the synergistic effect results mainly from the interaction of two irreversible fluxes, namely, the anodic dissolution current density and the plastic flowing in the surface layer caused by dynamic plastic deformation. An enhanced anodic dissolution flux is induced by the dynamic surface plastic deformation resulting from the impingement of solid particles, which can be correlated to the wastage rate due to the mechanical erosion. Meanwhile, the anodic current present at the electrode surface, in turn, can increase the mobility of dislocation and reduce the resistance in the surface layer against plastic deformation. Such an effect is demonstrated by the hardness degradation of metals in corrosive media. Theoretical analysis indicates that the corrosion-induced hardness degradation is a linear function of the logarithm of anodic current density. The degradation of mechanical erosion resistance with decreasing hardness suggests that the corrosion-enhanced erosion may result from the degradation in hardness of target material induced by the anodic dissolution and the corresponding wastage is also a linear function of the logarithm of anodic current density. The theoretical predictions were compared with the experimental results of carbon steels obtained form the slurry-erosion tests and the micro-hardness measurements. The results indicate that the hardness degradation in corrosive media is mainly controlled by the anodic current density and is almost independent of the polarization behavior of steels.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".