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Combining SWNT and Graphene in Polymer Nanofibers: A Route to Unique Carbon Precursors for Electrochemical Capacitor Electrodes. | LitMetric

It is important to fabricate nanostructured architectures comprised of functional components for a wide variety of applications because precise structural control in the nanometer regime can yield unprecedented, fascinating properties. Owing to their well-defined microstructural characteristics, it has been popular to use carbon nanospecies, such as nanotubes and graphene, in fabricating nanocomposites and nanohybrids. Nevertheless, it still remains hard to control and manipulate nanospecies for specific applications, thus preventing their commercialization. Herein, first, we report unique one-dimensional nanoarchitectures with meso-/macropores, consisting of single-walled nanotubes (SWNTs), graphene, and polyacrylonitrile, in which poly(vinyl alcohol) was employed as a dispersing agent and sacrificial porogen. One-dimensional SWNTs and two-dimensional graphene pieces were combined in the confined interior space of electrospun nanofibers, which led to unique microstructural characteristics such as enhanced ordering of SWNTs, graphene pieces, and polymer chains in the nanofiber interior. Next, the SWNT/graphene-in-polymer nanofiber (SGPNF) structures were converted into carbonized products (SGCNFs) with effective porosity and tunable electrochemical properties. Similar to SGPNFs, the microstructural and electrical properties of the SGCNFs depended on the incorporated amount of SWNT and graphene. At higher SWNT content, the mesopore volume proportion and specific discharge capacitance of the SGCNFs increased by max. 63 and 598%, respectively. The SGCNFs showed strong potential as a high-performance electrode material for electrochemical capacitors (max. capacitance: nonactivated ∼390 F g and activated ∼750 F g). Flexible, all solid-state capacitor cells based on SGCNFs were also successfully demonstrated as a model application. The SGCNFs can be further functionalized by various methods, which will impart attractive properties for extended applications.

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http://dx.doi.org/10.1021/acs.langmuir.8b03766DOI Listing

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