Facile Construction of N-Doped Graphene Supported Hollow PtAg Nanodendrites as Highly Efficient Electrocatalysts toward Formic Acid Oxidation Reaction
Bibliographic record
Abstract
The lack of cost-efficient catalysts for the electrooxidation of fuel in the anodic electrode has been a major barrier for the practical large-scale commercial application and hence needs to be optimized. Tuning the morphologies and structures of Pt-based bimetallic nanostructure plays a key role in controlling its interaction with reactants, and thus affects its electrocatalytic efficiency. In this regard, endowing the nanocatalysts with both of high surface active areas and controlled facets through modifying their surface compositions and morphologies can significantly enhance their electrocatalytic performances. To this end, we herein demonstrate a facile wet-chemical method to successfully construct the N-doped graphene supported hollow PtAg nanodendrites under the assistance of ultrasonic treatment. More importantly, the resulting N-doped graphene supported hollow PtAg nanodendrites show high performance for the electrooxidation of formic acid with the mass and specific activities of 1258.5 mA mg –1 and 6.14 mA cm –2, 3.77 and 1.57-fold enhancements than those of commercial Pt/C, respectively. It is believed that the as-prepared nanomaterials can be well-applied to serve as the highly efficient anode electrocatalysts for the commercial application of fuel cells and beyond.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".