Facile Synthesis of Lithium Sulfide@Carbon Nanocomposite via Precursor Solution Infiltration-Decomposition for High-Performance Lithium Sulfide Batteries
Bibliographic record
Abstract
Lithium–sulfur batteries (LSBs) based on lithium sulfide (Li 2 S), or Li 2 S-LSBs, are promising candidates for next-generation energy storage due to their high theoretical capacity, lower costs, and environmental benefits compared to lithium-ion batteries. However, synthesizing Li 2 S-infiltrated mesoporous carbon nanocomposites (Li 2 S@C) to mitigate the low conductivity of Li 2 S has been challenging because of its high melting point and poor solubility. To address this, we developed an efficient synthesis method for Li 2 S@C nanocomposites under mild conditions. Li 2 S was first reacted with carbon disulfide (CS 2 ) in ethanol at ambient temperature, forming a highly soluble lithium trithiocarbonate (Li 2 CS 3 ) solution, which was easily infiltrated into mesoporous Super P carbon (SP) to form a Li 2 CS 3 @C nanocomposite. Thermal decomposition of Li 2 CS 3 at 400 °C produced Li 2 S@SP-400 nanocomposites with finely dispersed Li 2 S particles (∼11 nm) confined within the SP matrix. The Li 2 S-LSBs exhibited a high discharge capacity of 821 mA h g –1 (Li 2 S) (equivalent to 1190 mA h g –1 (S) based on sulfur content) and demonstrated superior rate and cycling performance compared to commercial Li 2 S, noninfiltrated Li 2 S-400 nanoparticles, and sulfur nanocomposites (S@SP) prepared by melt infiltration. This simple, scalable method offers a promising route for commercializing high-energy-density Li 2 S-LSBs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".