Electrolysis of Ethanol and Methanol at PtRu@Pt Catalysts
Bibliographic record
Abstract
Electrolysis of ethanol in a proton exchange membrane (PEM) cell is an attractive method for generating hydrogen from renewable resources. However, the most active anode catalysts, such as PtRu, produce acetic acid as the main product, which makes the process very inefficient. Core–shell nanoparticles can improve efficiency by providing more selective cleavage of the C–C bond at a Pt shell. Here, the influence of the amount of Pt deposited onto a commercial PtRu/C catalyst has been investigated for electrochemical oxidation of ethanol and methanol, in aqueous H2SO4 at ambient temperature and in a PEM electrolysis cell at 80 °C. It is shown that addition of a Pt shell improves voltammetric activity markedly for both methanol and ethanol oxidation, while half-wave potentials in the PEM cell are shifted to higher potentials as the Pt coverage is increased. However, limiting currents for ethanol oxidation in the PEM cell are increased, and it is shown that the distribution of products shifts strongly towards CO2, which provides more efficient production of hydrogen.
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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) | 0.001 | 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) | 0.001 | 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".