Interpenetrating Triphase Cobalt‐Based Nanocomposites as Efficient Bifunctional Oxygen Electrocatalysts for Long‐Lasting Rechargeable Zn–Air Batteries
Bibliographic record
Abstract
Abstract Rational construction of atomic‐scale interfaces in multiphase nanocomposites is an intriguing and challenging approach to developing advanced catalysts for both oxygen reduction (ORR) and evolution reactions (OER). Herein, a hybrid of interpenetrating metallic Co and spinel Co3O4 “Janus” nanoparticles stitched in porous graphitized shells (Co/Co3O4@PGS) is synthesized via ionic exchange and redox between Co2+ and 2D metal–organic‐framework nanosheets. This strategy is proven to effectively establish highways for the transfer of electrons and reactants within the hybrid through interfacial engineering. Specifically, the phase interpenetration of mixed Co species and encapsulating porous graphitized shells provides an optimal charge/mass transport environment. Furthermore, the defect‐rich interfaces act as atomic‐traps to achieve exceptional adsorption capability for oxygen reactants. Finally, robust coupling between Co and N through intimate covalent bonds prohibits the detachment of nanoparticles. As a result, Co/Co3O4@PGS outperforms state‐of‐the‐art noble‐metal catalysts with a positive half‐wave potential of 0.89 V for ORR and a low potential of 1.58 V at 10 mA cm−2 for OER. In a practical demonstration, ultrastable cyclability with a record lifetime of over 800 h at 10 mA cm−2 is achieved by Zn–air batteries with Co/Co3O4@PGS within the rechargeable air electrode.
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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".