The Surfactant-Promoted Electroreduction of Oxygen to Hydrogen Peroxide
Bibliographic record
Abstract
The two-electron reduction of at pH 3 (1 M acidified by glacial acetic acid) and 9.6 (mixture of 0.5 M and 0.5 M was investigated in flow-by electrochemical reactors with three-dimensional cathodes, consisting of graphite felt (GF) or reticulated vitreous carbon (RVC). The cathode was operated with co-current upward gas/liquid flow and pressures in the range of 200-700 kPa. A factorial design with four variables at two levels was employed to investigate the effects of superficial current density, liquid load, pressure, and cationic surfactant concentration [ i.e. , trioctylmethylammonium chloride (Aliquat® 336, A336)] on concentration, current efficiency, and reactor voltage. Among the investigated variables A336 exerted the strongest positive main effect on both concentration and current efficiency. The beneficial effect of A336 was due to suppression of the loss by both electroreduction and surface-catalyzed decomposition. However, A336 increased the pressure gradient through GF by up to 100%. The surfactant effect on the pressure gradient was estimated using the Herbolzheimer-Park model for the influence of surfactant on the motion of gas bubbles in liquid-filled capillaries. An mass-transfer model in both GF and RVC was developed and correlated with the experimental results. © 2005 The Electrochemical Society. All rights reserved.
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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) | 0.000 | 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 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".