The DOI matches its Crossref record; 111 of the 111 references it cites were found in a registry or an index.
Biomass derived carbon for supercapacitor applications: Review
Abstract
Abstract The activated carbon based electrode materials are promising for applications in supercapacitors, fuel cells, and batteries due to their large surface area and porous structure. All the carbonaceous materials (CNTs, graphene, activated carbon) exhibit EDLCs type behavior based on the adsorption of ions at the electrode interface. On the other hand, the charge storage mechanism of pseudo-capacitive materials, including metal oxides and conducting polymers, is based on the rapid faradic reactions. Owing to this, the latter has a higher level of charge storage than the former, but at the same time, it suffers from a lack of conductivity and lowers cycle stability. To achieve a higher energy density for the supercapacitor without degrading its power density and cycle stability, one of the best solutions is to compound the carbon based materials with pseudocapacitive materials. This review briefly described the various carbon composites with metal oxides, but the main focus is on biomass-derived activated carbon for supercapacitor applications, as the green and sustainable source of energy is the demand of ever increasing global crisis. The ongoing challenges and future developments in this direction for building efficient energy storage systems are also addressed here.
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Cites
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Cited by
Biomass derived functional carbon materials for supercapacitor applications
Rawat, S., Mishra, R. K., & Bhaskar, T. (2022) · Chemosphere · doi:10.1016/j.chemosphere.2021.131961 · Cited by 296
Metadata
- Authors
- Saini, S., Chand, P., & Joshi, A.
- Venue
- Journal of Energy Storage
- Publisher
- Elsevier BV
- Published
- 2021-07
- Volume
- 39
- Pages
- 102646
- ISSN
- 2352-152X (ISSN-L)
- OpenAlex
- W3162109060
- Cited by
- 455
- References
- 111
- FWCI
- 16.04
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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