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Cited by 201

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Biomass-derived porous carbon materials for advanced lithium sulfur batteries

Liu, Poting, Wang, Yunyi, Liu, Jiehua·2019·Journal of Energy Chemistry

Abstract

Abstract Biomass, as the most widely used carbon sources, is the main ingredient in the formation of fossil fuels. Biomass-derived novel carbons (BDNCs) have attracted much attention because of its adjustable physical/chemical properties, environmentally friendliness, and considerable economic value. Nature contributes to the biomass with bizarre microstructures with micropores, mesopores or hierarchical pores. Currently, it has been confirmed that biomass has great potential applications in energy storage devices, especially in lithium-sulfur (Li–S) batteries. In this article, the synthesis and function of BDNCs for Li–S batteries are presented, and the electrochemical effects of structural diversity, porosity and surface heteroatom doping of the carbons in Li-S batteries are discussed. In addition, the economic benefits, new trends and challenges are also proposed for further design excellent BDNCs for Li–S batteries.

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Crossref · 10.1016/j.jechem.2018.10.005

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Metadata

Authors
Liu, P., Wang, Y., & Liu, J.
Venue
Journal of Energy Chemistry
Publisher
Elsevier BV
Published
2019-07
Volume
34
Pages
171-185
ISSN
2095-4956 (ISSN-L)
OpenAlex
W2907333246
Cited by
201
References
6
FWCI
5.55
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Biomass-derived porous carbon materials for advanced lithium sulfur batteries. https://app.cochat.ai/papers/10.1016/j.jechem.2018.10.005
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Liu, P., Wang, Y., & Liu, J. (2019). Biomass-derived porous carbon materials for advanced lithium sulfur batteries. Journal of Energy Chemistry. https://doi.org/10.1016/j.jechem.2018.10.005

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.