Bimetallic Hollow Tubular NiCoO<sub><i>x</i></sub> as a Bifunctional Electrocatalyst for Enhanced Oxygen Reduction and Evolution Reaction
Bibliographic record
Abstract
The development of high-efficiency oxygen electrocatalysts with earth-abundant transition metals rather than scarce noble metals has aroused growing interests due to their potential for energy storage and conversion applications. Herein, we developed a facile strategy to synthesize hollow tubular bimetallic Ni–Co oxide rooted with dense nanosheets for enhanced bifunctionality and facilitated redox reaction kinetics. Owing to the rational design of morphology and well-dispersed Ni and Co ions, the bimetallic samples exhibit admirable bifunctional electrocatalytic activities. This bimetallic Ni–Co oxide shows superior oxygen electrocatalytic performance in comparison with the monometallic Ni and Co oxides, according to the electrocatalytic synergistic effect from the bimetallic system. The optimized sample with the specific mass ratio of Ni and Co displays the oxygen reduction reaction (ORR) property comparable to commercial Pt/C and oxygen evolution reaction (OER) performance superior to commercial RuO 2 . The electrochemical tests and structural characterizations offer in-depth dissection on the electrocatalytic behaviors, especially the superb stability in both ORR and OER tests, as well as the outstanding resistance to methanol poisoning, representing a promising candidate in the renewable energy field.
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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".