Realizing Solid‐Phase Reaction in Li–S Batteries via Localized High‐Concentration Carbonate Electrolyte
Bibliographic record
Abstract
Abstract Lithium–sulfur (Li–S) batteries have attracted significant attention because of their high theoretical energy density and low cost. However, their poor cyclability caused by the shuttle effect in ether‐based electrolytes remains a great challenge for their practical application. Herein, a novel electrolyte is proposed by combining widely used carbonate solvents diethyl carbonate/fluoroethylene carbonate and inert diluent 1,1,2,2‐tetrafluoroethyl 2,2,3,3‐tetrafluoropropyl ether for Li–S batteries based on typical mesoporous carbon/sulfur (KB/S) materials. Differing from the conventional dissolution‐precipitation mechanism, the sulfur cathodes demonstrate a solid‐phase reaction route in the developed electrolyte, which is realized with the assistance of an in situ formed compact cathode electrolyte interface (CEI) film on the cathode caused by the nucleophilic reaction between lithium polysulfides (LiPSs) and carbonate solvents. The formed CEI film can effectively block the infiltration of carbonate solvents and can completely suppress the generation of LiPSs, thus eliminating the shuttle effect. As a result, the KB/S electrode demonstrates a stable cycling performance at 2 C by maintaining a discharge capacity of 570 mAh g –1 after 600 cycles, corresponding to an average capacity decay of 0.057% per cycle. More significantly, this strategy provides a new pathway toward future development of Li–S batteries based on solid‐phase conversion.
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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 | 0.001 |
| 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".