Engineering of a Low‐Cost, Highly Active, and Durable Tantalate–Graphene Hybrid Electrocatalyst for Oxygen Reduction
Bibliographic record
Abstract
Abstract The oxygen reduction reaction (ORR) is one of the most important reactions in renewable energy conversion and storage devices. The full deployment of these devices depends on the development of highly active, stable, and low‐cost catalysts. Herein, a new hybrid material consisting of Na 2 Ta 8 O 21− x /Ta 2 O 5 /Ta 3 N 5 nanocrystals grown on N‐doped reduced graphene oxide is reported. This catalyst shows a significantly enhanced ORR activity by ≈4 orders of magnitude in acidic media and by ≈2 orders of magnitude in alkaline media compared to individual Na 2 Ta 8 O 21− x on graphene. Moreover, it has excellent stability in both acid and alkaline media. It also has much better methanol tolerance than the commercial Pt/C, which is relevant to methanol fuel cells. The high ORR activity arises not only from the synergistic effect among the three Ta phases, but also from the concomitant nitrogen doping of the reduced graphene oxide nanosheets. A correlation between ORR activity and nitrogen content is demonstrated. Deep insights into the mechanism of the synergistic effect among these three Ta‐based phases, which boosts the ORR's kinetics, are acquired by combining specific experiments and density functional theory calculations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".