Nanoscale Encapsulation of Sulfur Cathodes via Self-Healing and Polar Synergistic Multifunctional Coating for High-Performance Li–S Batteries
Bibliographic record
Abstract
The development of lithium–sulfur (Li–S) batteries is plagued by serious polysulfide shuttling, sluggish redox reaction kinetics, and low sulfur utilization. In this work, a nanoscale poly(hindered urea) (PHU) coating with self-healability is designed for sulfur cathodes to achieve an improved electrochemical performance. The as-prepared polymer coating in a thickness of about 3 nm uniformly on the surface of the nanoscale sulfur/carbon (S/C) particles acts as a physical barrier to effectively encapsulate and accumulate lithium polysulfide (LiPS) inside the S/C nanoscale particles and thus facilitates the rapid conversion of LiPSs. In addition, the dynamic and reversible self-healing hindered urea bonds (HUBs) endow the PHU coating layer with the ability to maintain structural integrity and stability even after numerous cycles of volume expansion and shrinkage from nanoscale particles to the electrode level. More importantly, the polar groups carried by the PHU polymer exert a strong adsorption effect on LiPSs, thus further hindering the shuttling of LiPSs. Consequently, the nanoarchitecture with PHU coating layer exhibits impressive cycle stability (maintaining 82.8% capacity retention after 150 cycles at 0.5 C) and outstanding rate performance (capacity retention of 623.9 mAh g –1 at 2 C). Furthermore, even under a high sulfur loading of 8.47 mg cm –1, a high areal-specific capacity of 6.4 mAh cm –2 is still delivered.
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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".