Editors' Choice—Electrolyte Film Thickness Effects on the Cathodic Current Availability in a Galvanic Couple
Bibliographic record
Abstract
A combined modeling and experimental study was performed to understand the dependence of the cathodic current delivery capacity on the electrolyte film thickness and cathode size in a galvanic couple. The appropriate cathodic kinetics for the modeling were generated by use of a rotating disk electrode to simulate the electrolyte film thickness. These results provided boundary conditions for a finite element model which calculated the potential distribution along a metallic surface and the associated cathodic current supplied for electrolyte layers of varying thickness. The total cathodic current was then calculated through integration of the current density across the surface. Electrolyte layer domains were delineated by three limits which described, in order of decreasing film thickness, i) transition in exposure condition from full immersion to thick film, ii) the hydrodynamic boundary layer due to natural convection which defined the upper limit of the thin film regime, and iii) the relative dominance of ohmic resistance over mass transport in determining the total current output. This study also showed that for sufficiently thin films, this total current was independent of the size of the cathode and the nature of kinetics at the electrochemical interface, being solely driven by the ohmic resistance in solution.
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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 | 0.002 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".