Self-assembly formation of Bi-functional Co3O4/MnO2-CNTs hybrid catalysts for achieving both high energy/power density and cyclic ability of rechargeable zinc-air battery
Bibliographic record
Abstract
α-MnO2 nanotubes-supported Co3O4 (Co3O4/MnO2) and its carbon nanotubes (CNTs)-hybrids (Co3O4/MnO2-CNTs) have been successfully developed through a facile two-pot precipitation reaction and hydrothermal process, which exhibit the superior bi-functional catalytic activity for both ORR and OER. The high performance is believed to be induced by the hybrid effect among MnO2 nanotubes, hollow Co3O4 and CNTs, which can produce a synergetic enhancement. When integrated into the practical primary and electrochemically rechargeable Zn-air batteries, such a hybrid catalyst can give a discharge peak power density as high as 450 mW cm(-2). At 1.0 V of cell voltage, a current density of 324 mA cm(-2) is achieved. This performance is superior to all reported non-precious metal catalysts in literature for zinc-air batteries and significantly outperforms the state-of-the-art platinum-based catalyst. Particularly, the rechargeable Zn-air battery can be fabricated into all-solid-state one through a simple solid-state approach, which exhibits an excellent peak power density of 62 mW cm(-2), and the charge and discharge potentials remain virtually unchanged during the overall cycles, which is comparable to the one with liquid electrolyte.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".