Influence of Crack Tip Plasticity on the Microstructure and Corrosion Behavior of CA6NM Stainless Steel Measured Using Scanning Electrochemical Cell Microscopy (SECCM)
Bibliographic record
Abstract
The existence of cracks within ductile materials such as stainless steel induces local plasticity around the crack tip that may cause local changes in the microstructure. Although the plastic deformation and microstructural heterogeneities are expected to influence the electrochemistry of the area around the crack tip, few are the studies that correlate the factors- strain and corrosion- together. In this work, we analyze the corrosion behavior of pre-cracked CA6NM compact tension stainless steel samples taking into consideration the variations in the microstructure resulting from the local plasticity at the tip of a crack. Multiple surface microstructure analysis are obtained to characterize the surface properties of the plastic zone. The localized corrosion behavior around the crack tip is studied using the scanning electrochemical cell microscopy (SECCM) technique. The acquired micro open circuit potential (OCP) and micro potentiodynamic polarization (PDP) curves were used to generate corrosion potential and corrosion current maps of the scanned area. The electrochemical behavior of the crack tip was compared with that in the un-deformed area of the same sample. The ability to conduct direct electrochemical measurements at microscopic scale through SECCM allows to correlate the localized corrosion behavior to the microstructure analysis obtained before. This work paves the avenue to studying the synergistic effect of fatigue damage on the local corrosion behavior through monitoring both simultaneously.
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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) | 0.001 | 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".