Efficient Oxidation of Ethanol at Ru@Pt Core-Shell Catalysts in a Proton Exchange Membrane Electrolysis Cell
Bibliographic record
Abstract
Efficient electrochemical oxidation of ethanol in fuel cells and electrolysis cells is important for generating power and hydrogen, respectively, from renewable resources. PtRu alloys are most widely employed as catalysts because they provide high activities at low potentials. However, they produce acetic acid as the main product from ethanol, which results in low faradaic and overall efficiencies. In contrast, Pt provides high selectivity for the complete oxidation of ethanol to CO 2 , but low activities. Ru@Pt core–shell nanoparticles can improve efficiency by delivering higher activity than Pt and enhanced formation of CO 2 relative to PtRu. Here, Ru@Pt catalysts have been prepared by depositing Pt onto a commercial carbon-supported Ru catalyst. The influence of the amount of Pt deposited has been investigated in H 2 SO 4 (aq) at ambient temperature and in a proton exchange membrane cell at 80 °C. Activities for ethanol oxidation were intermediate between those for commercial Pt and PtRu catalysts, providing higher currents than Pt at low potentials, and higher currents than PtRu at high potentials. Faradaic yields of CO 2 (38%–48%) were greatly increased relative to the PtRu alloy catalyst (11%). This will optimize the efficiency of ethanol oxidation in PEM electrolysis and fuel cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".