Carbon Nanospheres with High Intra‐ and Inter‐Sphere Porosities for High‐Rate Energy‐Storage Applications
Bibliographic record
Abstract
Abstract Kinetic problems restrict the applications of carbon‐based materials in energy‐storage systems at high currents. Herein, small carbon nanospheres (5 and 20 nm in average diameter) featured with high intra‐sphere micro‐/meso‐porosity and inter‐sphere meso‐/macro‐porosity are demonstrated as high‐rate anode materials for lithium‐ion batteries (capacity retention: 42.3 % at 1 A g−1 relative to 0.05 A g−1), enabling rapid lithium‐ion diffusion with shortened diffusion lengths. Additionally, the rapid lithium‐ion response is also verified with their superior capacitance retention at high currents as electrode materials for electrical double layer capacitors (capacitance retention: 69.2 % at 100 A g−1 relative to 0.5 A g−1). Our results confirm the optimum energy‐storage performance of this class of nanocarbons with hierarchical micro‐/meso‐/macro‐porous structures.
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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".