Tailoring Porosity in Carbon Nanospheres for Lithium–Sulfur Battery Cathodes
Bibliographic record
Abstract
Porous hollow carbon spheres with different tailored pore structures have been designed as conducting frameworks for lithium-sulfur battery cathode materials that exhibit stable cycling capacity. By deliberately creating shell porosity and utilizing the interior void volume of the carbon spheres, sufficient space for sulfur storage as well as electrolyte pathways is guaranteed. The effect of different approaches to develop shell porosity is examined and compared in this study. The most highly optimized sulfur-porous carbon nanosphere composite, created using pore-formers to tailor shell porosity, exhibits excellent cycling performance and rate capability. Sulfur is primarily confined in 4-5 nm mesopores in the carbon shell and inner lining of the shells, which is beneficial for enhancing charge transfer and accommodating volume expansion of sulfur during redox cycling. Little capacity degradation (∼0.1% /cycle) is observed over 100 cycles for the optimized material.
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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 | 0.001 |
| 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".