Iron- and Nitrogen-Functionalized Graphene Nanosheet and Nanoshell Composites as a Highly Active Electrocatalyst for Oxygen Reduction Reaction
Bibliographic record
Abstract
In this work, we develop a simple method to thermally synthesize a nonprecious metal-based nitrogen-doped graphene (NG) electrocatalyst using exfoliated graphene (Ex-G) and urea with varying amounts of iron (Fe) precursor. The morphology and structural features of the synthesized electrocatalyst (Fe-NG) were characterized by SEM and TEM, revealing the existence of graphitic nanoshells that potentially contribute to the ORR activity by providing a higher degree of edge plane exposure. The surface elemental composition of the catalyst was analyzed through XPS, which showed a high content of a total N species (∼8 at. %), indicative of the effective N-doping, present mostly in the form of pyridinic nitrogen groups. The oxygen reduction reaction (ORR) performance of the catalyst was evaluated by rotating disk electrode voltammetry in alkaline electrolyte and in a zinc-air battery cell. Fe-NG demonstrated high onset and half-wave potentials of −0.023 V (vs SCE) and −0.110 V (vs SCE), respectively. This excellent ORR activity is translated into practical zinc-air battery performance capabilities approaching that of commercial platinum-based catalyst.
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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 | 0.000 |
| 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 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".