Sulfur-Infiltrated Hierarchical Porous Carbon (HPC) Cathodes for Lithium-Sulfur Batteries
Bibliographic record
Abstract
Lithium sulfur (Li-S) batteries have been considered as promising candidates for next-generation battery applications because of its high theoretical capacity (1675 mAh/g is 5 times higher than those of traditional cathode materials based on transition metal oxides or phosphates), abundance, safety, low cost, and eco-friendliness. However, the practical implementation of Li-S batteries is greatly hindered by the high resistance of sulfur (5 x 10-30 S cm-1 at 25 oC) and dissolution of soluble long-chain lithium polysulfides (Li2Sn, 4≤n≤8) in the polar organic electrolytes, and volume expansion of sulfur during discharge process, resulting in an insufficient cycle life. To this end, a number of studies have focused mainly on the development of carbon-sulfur composite with the intention to improve the cycle stability. Many types of mesoporous carbon materials have been studied as the electrically conducting host materials for improving the electrical conductivity of sulfur and preventing dissolution of soluble long-chain lithium polysulfides, which are intermediates formed as reaction in both discharge and charge processes in the electrolytes. Those approaches improve the electrical conductivity of sulfur, but are associated with inherent limitation of the dissolution of polysulfides due to the limitation of physical adsorption of the polysulfides by mesopores, which tends to limit the electrochemical performance of carbon-sulfur composite cathode materials. Recently, to overcome these problems, microporous carbon materials have been designed. Although the characterization of sulfur confined in micropores is not completely determined, the micropores have indeed turned out to be efficacious in mitigation of the soluble lithium polysulfides via various mechanisms: (1) strong adsorption of soluble polysulfides, (2) construction of solvent-free environment, and (3) formation of insoluble small S2-4 molecules. Because of these attributes, the microporous carbon-sulfur composites show outstanding cycling performance and rate capability. Additionally, Manthiram et al. reported a novel Li-S cell configuration having carbon interlayers with micropores between the separator and the regular sulfur electrodes. This interlayer works as polysulfide stockroom to maintain the cycle stability. Based on these micropore approaches, we combined sulfur encapsulation and micropores into a single electrode component by developing a hierarchical porous carbon (HPC) structure. In the HPC structure prepared by spray pyrolysis process, the inner meso- and macro- pores are surrounded by outer carbon shell with micropores. Hence, stable cycling was achieved by the outer micropores that shut dissolution of lithium polysulfides down, while most of active sulfur was loaded in the larger inner pores.
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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) | 0.001 | 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".