Walnut‐Like Multicore–Shell MnO Encapsulated Nitrogen‐Rich Carbon Nanocapsules as Anode Material for Long‐Cycling and Soft‐Packed Lithium‐Ion Batteries
Bibliographic record
Abstract
Abstract Metal oxide‐based nanomaterials are widely studied because of their high‐energy densities as anode materials in lithium‐ion batteries. However, the fast capacity degradation resulting from the large volume expansion upon lithiation hinders their practical application. In this work, the preparation of walnut‐like multicore–shell MnO encapsulated nitrogen‐rich carbon nanocapsules (MnO@NC) is reported via a facile and eco‐friendly process for long‐cycling Li‐ion batteries. In this hybrid structure, MnO nanoparticles are uniformly dispersed inside carbon nanoshells, which can simultaneously act as a conductive framework and also a protective buffer layer to restrain the volume variation. The MnO@NC nanocapsules show remarkable electrochemical performances for lithium‐ion batteries, exhibiting high reversible capability (762 mAh g −1 at 100 mA g −1 ) and stable cycling life (624 mAh g −1 after 1000 cycles at 1000 mA g −1 ). In addition, the soft‐packed full batteries based on MnO@NC nanocapsules anodes and commercial LiFePO 4 cathodes present good flexibility and cycling stability.
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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".