Controllable Urchin‐Like NiCo<sub>2</sub>S<sub>4</sub> Microsphere Synergized with Sulfur‐Doped Graphene as Bifunctional Catalyst for Superior Rechargeable Zn–Air Battery
Bibliographic record
Abstract
Abstract Rechargeable zinc–air batteries (ZnABs) are attracting great interest due to their high theoretical specific energy, safety, and economic viability. However, their performance and large‐scale practical applications are largely limited by poor durability and high overpotential on the air‐cathode due to the slow kinetics of the oxygen reduction and evolution reactions (ORR/OER). Therefore, it is highly desired to exploit an ideal bifunctional catalyst to endow the obtained ZnABs with excellent ORR/OER catalytic performances. Herein, a new nonprecious‐metal bifunctional catalyst of urchin‐like NiCo 2 S 4 microsphere synergized with sulfur‐doped graphene nanosheets (S‐GNS/NiCo 2 S 4 ) is controllably designed and synthesized by simply tailoring the structure and electronic arrangement, which endow the as‐prepared catalyst with excellent electroactivity and long‐term durability toward ORR and OER. Importantly, ZnABs constructed by this outstanding catalyst exhibit high power density, small charge/discharge voltage gap, and excellent cycle stability, notably outperforming the more costly commercial Pt/C + Ir/C mixture catalyst. These excellent electrocatalytic performances together with the simplicity of the synthetic method, make the urchin‐like NiCo 2 S 4 microsphere/S‐GNS hybrid nanostructure exhibit great promise as a superior air‐cathode catalyst for high‐performance rechargeable ZnABs.
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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) | 0.001 | 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".