Pt/Ru–Sn Oxide/Carbon Catalysts for Ethanol Oxidation
Bibliographic record
Abstract
Mixed Ru–Sn oxides have been deposited onto a high surface area carbon support by thermal decomposition of Ru and Sn acetylacetonate (acac) complexes. Adsorption of preformed Pt nanoparticles produced catalysts with enhanced low potential activity for the oxidation of ethanol in aqueous sulfuric acid at ambient temperature and in a proton exchange membrane (PEM) cell at 80 °C. Varying the oxide composition between Ru0.38Sn0.62O2 and Ru0.67Sn0.33O2 did not influence the catalyst’s activity greatly but did increase stability in the sulfuric acid solution. Higher stability was observed in the PEM cell, where a Pt/Ru0.55Sn0.45O2/C anode provided much higher currents than a commercial Pt/C catalyst for ethanol oxidation at low potentials. Anodes for direct ethanol fuel cells can be fabricated by coating a carbon fibre paper backing layer consecutively with carbon black, Ru(acac)3 + Sn(acac)2, and Pt nanoparticles, with appropriate thermal processing.
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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) | 0.001 | 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".