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Cited by 475

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Tailoring Porosity in Carbon Nanospheres for Lithium–Sulfur Battery Cathodes

He, Guang, Evers, Scott, Liang, Xiao, Cuisinier, Marine, Garsuch, Arnd, Nazar, Linda F.·2013·ACS Nano

Abstract

Porous hollow carbon spheres with different tailored pore structures have been designed as conducting frameworks for lithium-sulfur battery cathode materials that exhibit stable cycling capacity. By deliberately creating shell porosity and utilizing the interior void volume of the carbon spheres, sufficient space for sulfur storage as well as electrolyte pathways is guaranteed. The effect of different approaches to develop shell porosity is examined and compared in this study. The most highly optimized sulfur-porous carbon nanosphere composite, created using pore-formers to tailor shell porosity, exhibits excellent cycling performance and rate capability. Sulfur is primarily confined in 4-5 nm mesopores in the carbon shell and inner lining of the shells, which is beneficial for enhancing charge transfer and accommodating volume expansion of sulfur during redox cycling. Little capacity degradation (∼0.1% /cycle) is observed over 100 cycles for the optimized material.

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Metadata

Authors
He, G., Evers, S., Liang, X., Cuisinier, M., Garsuch, A., & Nazar, L. F.
Venue
ACS Nano
Published
2013-11-14
Volume
7
Issue
12
Pages
10920-10930
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2327001674
Cited by
475
References
2
FWCI
28.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Tailoring Porosity in Carbon Nanospheres for Lithium–Sulfur Battery Cathodes. https://app.cochat.ai/papers/10.1021/nn404439r
The paper
He, G., Evers, S., Liang, X., Cuisinier, M., Garsuch, A., & Nazar, L. F. (2013). Tailoring Porosity in Carbon Nanospheres for Lithium–Sulfur Battery Cathodes. ACS Nano. https://doi.org/10.1021/nn404439r

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.