Enhanced Catalytic Activity for the Ethanol Oxidation Reaction (EOR) using Novel Pt-Fe3O4/MWCNT Bimetallic Electrocatalyst
Bibliographic record
Abstract
In this work, 20% Pt-Fe3O4/MWCNT (Pt:Fe3O4 weight ratio of 80:20) and 20% Pt/MWCNT nanoparticles were synthesized and characterized as anode electrocatalysts in H2SO4 media. First, the electrocatalyst were submitted to accelerated catalyst degradation test (ACDT) by performing 500 cycles between 0.6 and 1.2 V (vs. SHE). Then, their performance for the EOR was evaluated. The magnetite-containing nanoparticles demonstrated to be highly electrochemically stable, with negligible surface area losses (less than 7%) in thehydrogen adsorption/desorption region. Moreover, Pt-Fe3O4/MWCNT showed a significantly enhanced catalytic activity for the EOR when compared to Pt/MWCNT, with almost 46% increase in current density when using Fe3O4 as co-catalysts.
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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".