Co-N-Doped Directional Multichannel PAN/CA-Based Electrospun Carbon Nanofibers as High-Efficiency Bifunctional Oxygen Electrocatalysts for Zn–Air Batteries
Bibliographic record
Abstract
A reasonable design of the pore structure of carbon nanofiber-based electrocatalysts can effectively accelerate the slow kinetics of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). In this study, we report an electrospinning method by adding supramolecular coordination polymers to selected polyacrylonitrile (PAN) and cellulose acetate (CA) spinning systems. Benefiting from the difference in the thermal decomposition temperature of each component during the pyrolysis process, CA was applied as a sacrificial template to prepare a high-efficiency ORR/OER bifunctional electrocatalyst (Co-N@PCNFs-0.2) with directional hollow channels and a hierarchical pore structure. This unique multichannel carbon nanofiber morphology and hierarchical pore structure led to abundant active sites while also boosting the electron transfer rates. Notably, applying Co-N@PCNFs-0.2 as an air electrode to Zn–air batteries results in a large specific discharge capacity of 884 W h kgZn–1 and a maximum power density of 151 mW cm–2.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".