Pt-CeOx/MWCNT electrocatalysts as ethanol-tolerant ORR cathodes for Direct Alcohol Fuel Cells
Bibliographic record
Abstract
High performance 20% Pt-CeOx (1:1 Pt:Ce weight ratio) electrocatalyst dispersed on Multiwalled Carbon Nanotubes (MWCNTs) was synthesized under H2 atmosphere at 300 °C. The average particle size determined from XRD was ca. 1.7 and 10 nm for Ce and Pt, respectively. HRTEM analysis confirmed the presence of particle sizes within this range, although it was not possible to distinguish Ce from Pt nanoparticles. The XPS spectrum of Ce showed characteristics that indicate the existence of both oxidized and reduced phases (i.e., Ce2O3 and CeO2). It is suggested that the presence of the C3+ state establishes the capacity of this material to act as a tolerant cathode. The spectrum of Pt confirmed the presence of Pt metal. The 20% Pt-CeOx/MWCNT cathode showed high electroactivity for the Oxygen Reduction Reaction (ORR). Moreover, this novel material presented a high degree of tolerance to ethanol. During polarization tests in ethanol-containing solution, the Pt-CeOx/MWCNT cathode showed no peak current density due to the ethanol oxidation reaction (EOR) and the onset potential for the ORR shifted by only 80 mV towards more negative potentials. Thus, the presence of ceria clearly enhanced the electrochemical tolerance of the Pt-based cathode to ethanol.
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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) | 0.000 | 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 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".