High‐Performance Zinc‐Air Batteries Based on Bifunctional Hierarchically Porous Nitrogen‐Doped Carbon
Bibliographic record
Abstract
Abstract Active and durable bifunctional electrocatalysts for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) on the cathode are required for high‐performance rechargeable metal‐air batteries. Herein, the synthesis of hierarchically porous nitrogen‐doped carbon (HPNC) with bifunctional oxygen electrocatalysis for Zn‐air batteries is reported. The HPNC catalyst possesses a large surface area of 1459 m2 g−1 and exhibits superior electrocatalytic activity toward ORR and OER simultaneously with a low OER/ORR overpotential of 0.62 V, taking the difference between the potential at 10 mA cm−2 for OER and half‐wave potential for ORR in 0.1 m KOH. Adopting HPNC as the air cathode, primary and rechargeable Zn‐air batteries are fabricated. The primary batteries demonstrate a high open‐circuit potential of 1.616 V, a specific capacity of 782.7 mAh gZn−1 and a superb peak power density of 201 mW cm−2. The rechargeable batteries can be cycled stably for over 360 cycles or 120 h at the current density of 5 mA cm−2. As elucidated by density functional theory, N‐doping is preferred on defective sites with pentagon configuration and on the edge in the form of pyridinic‐N‐type. The high content of these two motifs in HPNC leads to the superior ORR and OER activities, respectively.
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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".