Simulation-Based Approach to Determining Electron Transfer Rates Using Square-Wave Voltammetry
Bibliographic record
Abstract
The efficiency with which square-wave voltammetry differentiates faradic and charging currents makes it a particularly sensitive electroanalytical approach, as evidenced by its ability to measure nanomolar or even picomolar concentrations of electroactive analytes. Because of the relative complexity of the potential sweep it uses, however, the extraction of detailed kinetic and mechanistic information from square-wave data remains challenging. In response, we demonstrate here a numerical approach by which square-wave data can be used to determine electron transfer rates. Specifically, we have developed a numerical approach in which we model the height and the shape of voltammograms collected over a range of square-wave frequencies and amplitudes to simulated voltammograms as functions of the heterogeneous rate constant and the electron transfer coefficient. As validation of the approach, we have used it to determine electron transfer kinetics in both freely diffusing and diffusionless surface-tethered species, obtaining electron transfer kinetics in all cases in good agreement with values derived using non-square-wave methods.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".