Trapping and Redistribution of Hydrophobic Sulfur Sols in Graphene–Polyethyleneimine Networks for Stable Li–S Cathodes
Bibliographic record
Abstract
Abstract The lithium–sulfur battery is a promising next‐generation rechargeable battery system which promises to be less expensive and potentially fivefold more energy dense than current Li‐ion technologies. This can only be achieved by improving the sulfur utilization in thick, high areal loading cathodes while minimizing capacity fading to realize high practical energy densities and long cycle‐life. This study reports a simple method to fabricate a high capacity, high loading cathode with one of the highest cycle‐stabilities reported. It is demonstrated that sulfur sols formed by crashing dissolved elemental sulfur into water are trapped between graphene oxide sheets when flocculated with polyethyleneimine. Low temperature, hydrothermal treatment produces a conductive, partially covalent composite exhibiting outstanding cycle‐stability. Using this method, sulfur can be uniformly distributed at fractions as high as 75.7 wt%. Electrodes with high areal sulfur loadings (up to ≈5.4 mg cm −2 ), prepared using these composites, lead to projected high cell level practical energy densities of 400 Wh kg −1 . The electrodes demonstrate negligible capacity loss over 250 cycles at 0.15 C and only 0.028% capacity loss per cycle over 810 cycles at 0.75 C. Eventual capacity fading is found to be linked to degradation of lithium‐metal anode suggesting that the cathode material remains stable over even more extended cycling.
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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) | 0.000 | 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".