Li-S Cathodes with Extended Cycle Life By Sulfur Encapsulation in Disordered Micro-Porous Carbon Powders
Bibliographic record
Abstract
Sulfur cathodes have excellent theoretical properties for use as positive electrodes in rechargeable lithium batteries, but lack long-term stability required of practical secondary battery systems. To deal with this issue, high capacity Lithium-Sulfur cathodes with extended cycle life were prepared through thermal encapsulation of sulfurat 155°C in disordered micro-porous carbon powders that have high specific surface-area of ~ 2000 m2/g. The electrodes have been characterized using X-ray diffraction (XRD), Scanning electron microscopy/energy-dispersive X-ray (SEM/EDX), Raman spectroscopy, Thermal Gravimetric Analysis (TGA) and Gas adsorption technique. By using microporous carbon as matrices for sulfur cathodes and lithium nitrate as an additive to the electrolyte solution, that suppresses the shuttle phenomena in Li-sulfur batteries, we managed to achieve a reversible capacity of over 500mAh/g after 1000 cycles (Figure 1) with a Columbic efficiency approaching 100% throughout cycling. The sulfur composite cathodes of 14mm in diameter (area of ~1.54 cm2) and active material load of more than 1mg/cm2were tested in a two electrodes configuration with coin-type cells (2523,NRC, Canada). Electrolyte solution was DOL and DME (1:1 ratio) with 10% LiTFSI and 2% of LiNO3(by weight). The influence of the volume of the electrolyte solutions in Li-S cells was further evaluated by analyzing their voltage profiles during cycling.
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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 | 0.000 |
| 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 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".