CoNi Nanoparticle-Decorated ZIF-67-Derived Hollow Carbon Cubes as a Bifunctional Electrocatalyst for Zn–Air Batteries
Bibliographic record
Abstract
CoNi nanoparticle-decorated hollow carbon cubes (CoNi-HCCs) were synthesized using ZIF-67 as a sacrificial template. The synthesis utilizes the thermal instability of ZIF-67, creating hollow carbon nanostructures while facilitating carbonization and introducing metal nanoparticles (e.g., CoNi). Prototype Zn–air batteries equipped with CoNi-HCCs exhibited a promising discharge potential of 1.21 V and a charge potential of 2.04 V at 20 mA cm –2 . These values are superior to those of Pt–Ru, whose discharge and charge potentials were 1.20 and 2.08 V, respectively. CoNi-HCCs also displayed a high peak power density of 159.6 mW cm –2, which is significantly higher than the value for Pt–Ru (120.2 mW cm –2 ). After 90 h of bifunctional cycling at 10 mA cm –2, CoNi-HCCs only experienced an efficiency loss of 3.4% and maintained 55.3% battery efficiency, much more durable than Pt–Ru (41.7% after only 60 h).
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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".