Degradations of Mechanical Properties in Surface Layer and Erosion Resistance of Carbon Steel in Slurries with Different pH and Chemical Compositions
Bibliographic record
Abstract
Abstract Effects of anodic dissolution in corrosive slurries with different chemical compositions and pHs on the in-situ surface mechanical properties and slurry erosion resistance of carbon steel are investigated. The experimental measurements indicate that the materials loss rate due to corrosion-enhanced erosion increases linearly with the logarithm of anodic current density. The in-situ nanoindentation shows that the presence of anodic current on surface reduces the surface hardness. Under the galvanostatic control, the erosion rates in acidic slurries are much higher than those in the neutral and alkaline slurries. The exposure to the acidic solutions can also lead to a larger in-situ surface hardness reduction than those than those observed in neutral and alkaline solutions. In the neutral and alkaline corrosive media, the erosion rates and the in-situ surface hardness degradation are hardly affected by the chemical composition of aqueous media. The agreement in the high-to-low order of the in-situ surface hardness and the erosion wastage under the galvanostatic control suggests the corrosion-induced surface mechanical property degradation may play a role in the mechanism of corrosion-enhanced erosion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".