Study of Ethanol Electrooxidation Reaction at Room Temperature on Nanometric Pt-Ru, Pt-Sn and Pt-Ru-Sn in Direct Alcohol Fuel Cells
Bibliographic record
Abstract
Ethanol electrooxidation in acid medium was investigated on Pt-Ru-Sn/C, Pt-Ru/C and Pt-Sn/C. The electrocatalysts were synthesized by microwave assisted chemical reduction reaction. The samples were characterized by transmission electron microscopy (TEM), X-ray diffraction analysis (XRD) and electrochemical analysis for the electrooxidation of ethanol. The ternary electrocatalyst was evaluated in an experimental Direct Ethanol Fuel Cell (DEFC). The method of synthesis used in this work allowed the formation of nanostructured electrocatalysts. The results obtained by electrochemical studies showed that the ternary system Pt-Ru-Sn/C exhibited the highest activity with respect to the binary systems Pt-Ru/C and Pt-Sn/C for carrying out the ethanol electrooxidation reaction. 0.4 mg∙cm-2 of electrocatalytic load of Pt-Ru-Sn/C was placed in the anode of an experimental fuel cell operating at room temperature. It was possible to obtain a power density of 0.14, 0.12 and 0.11 mW∙cm-2 after 20, 40 and 60 minutes respectively. The experiments were carried out at a controlled temperature of 297 K and they showed the feasibility to produce electricity at room temperature by using this ternary electrocatalyst in Direct Ethanol Fuel Cells.
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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".