Use of EIS to Measure the Rate of H<sub>2</sub>O<sub>2</sub>Decomposition on a Bulk Magnetite Electrode in Alkaline Solution
Bibliographic record
Abstract
The new generation of supercritical cooled water reactors (SCWR) are susceptible to particulate fouling as a result of corrosion product sedimentation. Iron oxides are a major component of corrosion products and are also known to catalyze hydrogen peroxide decomposition. This work aimed to investigate the rate of H2O2 decomposition on the surface of a magnetite bulk electrode by using electrochemical impedance spectroscopy. A magnetite bulk electrode was immersed in a suspension of various concentrations of magnetite particles and initial H2O2 concentration of 10−2 M. It was observed that the electrochemical response of the magnetite surface (which is partially oxidized to γ − Fe+3 species) is a function of H2O2 concentration. Therefore, at different time intervals EIS was used to obtain charge transfer resistance as a proxy variable for hydrogen peroxide concentration. These measurements were compared to results obtained by permanganate titration. It was observed that the changes of decomposition current density extracted from the EIS data fitting process for various conditions were in good agreement with the titration results. H2O2 decomposition in the presence of iron oxide particles was found to be a second-order reaction with rate constants of 0.015 and 0.017 min−1g−1L (obtained from EIS and titration methods, respectively).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".