Methyl Viologen as a Redox Mediator for Scanning Electrochemical Microscopy to Study Copper Corrosion Under Deaerated Conditions
Bibliographic record
Abstract
Scanning electrochemical microscopy (SECM) is a popular tool to study corrosion with high spatial resolution. The feedback mode of SECM involves the use of an added redox mediator in solution to probe local surface kinetics. Depending on the redox mediator's oxidation state and formal potential, as well as the corroding metal's corrosion potential, the electroactive species can potentially polarize the substrate and alter the corrosion behavior at the macro and/or microscale. Therefore, the choice of redox mediator is material dependent. This study explored the use of methyl viologen (MV) as a potentially ideal redox mediator for studying the local reactivity of copper. The SECM solutions were deaerated prior to SECM approach curve measurements to avoid a convoluted response from the oxygen reduction reaction at the ultramicroelectrode. Since the formal potential of MV is lower than the corrosion potential of Cu and undergoes oxidation to regenerate at the substrate's surface, the redox mediator was successfully implemented for kinetic measurements without inducing oxidative etching, ultramicroelectrode fouling, or macroscale corrosion. This work highlights the importance of redox mediator choice for SECM corrosion studies to avoid misinterpretation of data and provides a systematic method of making such decision for accurate measurements.
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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 | 0.001 |
| 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".