Product Distributions and Efficiencies for Ethanol Oxidation in a Proton Exchange Membrane Electrolysis Cell
Bibliographic record
Abstract
The stoichiometry, efficiency, and product distribution for ethanol oxidation in fuel cell hardware has been determined at 80°C for commercial Pt/C, PtRu/C and PtSn/C anode catalysts. The amounts of ethanol consumed and acetic acid and acetaldehyde produced were determined by proton NMR spectroscopy while CO 2 was measured with a non-dispersive infrared CO 2 monitor. The Pt/C catalyst was most selective for the complete oxidation of ethanol to CO 2 at all potentials and therefore produced the highest number of electrons per ethanol molecule (stoichiometry). Consequently, it would provide the highest efficiency for a fuel cell, and for an electrolysis cell at high current densities. However, PtRu/C provided much higher currents at low overpotentials and therefore better electrolysis efficiency than Pt/C at low current densities. The main product at the PtRu/C catalyst was acetic acid, with ≥ 86% conversion at potentials ≥ 0.35 V vs. a dynamic hydrogen electrode. The PtSn/C catalyst also provided high yields of acetic acid (65–75%), with substantial production of CO 2 (26–27%) at high potentials.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".