Electrocatalysis of S-doped carbon with weak polysulfide adsorption enhances lithium–sulfur battery performance
Bibliographic record
Abstract
Heteroatom-doped nanocarbons are beneficial for the performance improvement of lithium-sulfur batteries, and the reason is usually attributed to their strong adsorption to the soluble polysulfides. Herein, we found that, despite the weak polysulfide adsorption on hierarchical S-doped carbon nanocages (hSCNCs), the hSCNC-encapsulated sulfur cathode still exhibited better performance than the counterpart using undoped carbon nanocages, showing a high capacity of 579 mA h g-1 at 2 A g-1 after 400 cycles, and a high areal capacity of 4.7 mA h cm-2 with a high sulfur loading of 4.5 mg cm-2. The electrocatalysis-promoted mechanism of S-doped carbon was demonstrated, which facilitated polysulfide conversion and suppressed the polarization effect, thereby leading to superior performance.
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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".