Micro-Electrochemical Characterization of the Synergism of Hydrogen and Stress in Anodic Dissolution of Steel and Its Implication on Pipeline Stress Corrosion Cracking
Bibliographic record
Abstract
Localized electrochemical impedance spectroscopy (LEIS) technique was used to investigate the effects of stress and hydrogen as well as their synergism on anodic dissolution of steel under near-neutral pH condition where pipeline stress corrosion cracking (SCC) has been reported. There exists a threshold stress value, under which there is little effect of applied stress on anodic dissolution of steel. Above the value, the dissolution rate of steel increases with the stress. Hydrogen-charging enhances anodic dissolution of steel, which is attributed to the effect of hydrogen on the formation of corrosion product layer and the activation of the steel. The stress effect factor and the stress-hydrogen synergism effect factor are quantified. A detailed analysis shows that the synergism of stress and hydrogen at crack tip is expected to play an important role in near-neutral pH SCC of pipelines.
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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 | 0.000 |
| 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 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".