Enhanced cycling stability in Li-S batteries: CR-CTA modified GF separators with mechanistic insights and performance evaluation
Bibliographic record
Abstract
Lithium-sulfur (Li-S) batteries offer high theoretical energy density but face challenges like polysulfide dissolution and poor cycling stability. This study presents an innovative approach to improving Li-S battery performance by modifying glass fiber (GF) separators with a compound (CR-CTA) prepared from Congo Red (CR), a redox-active organic compound, and cetyltrimethylammonium bromide (CTAB), a cationic surfactant. The CR-CTA/SP/PVP-modified GF separator significantly enhances electrochemical properties, cycling stability, and ion transport, reducing the polysulfide shuttle effect and improving sulfur utilization. A Li-S battery using the CR-CTA/SP/PVP-modified GF separator achieved an initial capacity of 1153 mAh g −1 and retained 994 mAh g −1 (86.2 %) after 300 cycles at 0.5C. These results suggest that redox-active molecules like CR can serve as effective functional additives for separator modification, paving the way for high-performance energy storage devices. • CR-CTA-modified GF separator enhances Li-S battery cycling stability. • Innovative CR-CTA compound mitigates polysulfide shuttle effect in Li-S batteries. • Significant boost in sulfur utilization and long-term cycling efficiency. • Dual-modified separator shows 85.6 % capacity retention after 300 cycles. • Redox-active CR in separator improves ion transport and battery performance.
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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 | 0.001 | 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) | 0.000 | 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".