Nanoscale Fe3O4 Electrocatalysts for Oxygen Reduction Reaction
Bibliographic record
Abstract
This study presents a straightforward hydrothermal synthesis approach to fabricate uniform and highly dispersed nanoscale Fe3O4 electrocatalysts for the oxygen reduction reaction (ORR). FeSO4·7H2O is used as the precursor, and sodium dodecyl sulfate (SDS) is incorporated as a dispersing agent to optimize particle size and dispersion. The SDS concentration plays a crucial role in controlling the particle size and distribution, with higher SDS concentrations resulting in smaller, well-dispersed particles (30–40 nm), compared to the agglomerated particles formed without SDS. The Fe3O4 catalyst demonstrates significant enhancement in ORR performance, with a half-wave potential of 0.091 V vs. Hg/HgO and a limiting diffusion current density of −5.50 mA cm2, surpassing the performance of agglomerated Fe3O4 and approaching that of state-of-the-art 20% Pt/C catalysts. Additionally, the Fe3O4 catalyst exhibits superior stability and resistance to methanol and CO poisoning, presenting a promising alternative to platinum-based catalysts for ORR applications. This work introduces an efficient approach for the synthesis of high-performance and evenly distributed Fe3O4 electrocatalysts, offering a new pathway for the development of metal oxide-based ORR catalysts with enhanced activity and durability.
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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".