Hierarchically porous carbon derived from biomass: Effect of mesopore and heteroatom-doping on electrochemical performance
Source abstract
Abstract
Abstract Two kinds of porous carbons derived from Osmanthus fragrans and Sterculia lychnophora, respectively, are prepared by hydrothermal carbonization and KOH activation. The characterizations of electron microscopy and N2 adsorption-desorption isotherms show that both Osmanthus fragrans-derived porous carbon and Sterculia lychnophora-derived porous carbon have the hierarchical micro/meso/macroporous structure with interpenetrating network, but pore structure is mainly the micropore for Osmanthus fragrans-derived porous carbon, while more mesopore for Sterculia lychnophora-derived porous carbon. The surface chemical analysis reveals that Sterculia lychnophora-derived porous carbon has C N and more oxygen-containing groups in comparison with the Osmanthus fragrans-derived porous carbon. When used as electrode materials for EDLC, the Sterculia lychnophora-derived porous carbon electrodes deliver higher specific capacitance, higher capacitance retention and better cycling stability than Osmanthus fragrans-derived porous carbon. The superior electrochemical performance of Sterculia lychnophora-derived porous carbon is mainly attributed to the abundant mesopore, doping of N atom as well as more oxygen-containing groups. Finally, symmetrical supercapacitors are assembled by Sterculia lychnophora-derived porous carbon electrodes and release a high energy density of 9.58 W h kg−1 with a powder density of 500 W kg−1. The results showed that preparation of porous carbon materials from biomass is effectively procedure to improve high performance ELDC devices, and the selection of biomass precursors is the key in the preparation high performance electrode materials for ELDC.
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Research context
OpenAlex topics: Supercapacitor Materials and Fabrication · Advanced battery technologies research · Electrocatalysts for Energy Conversion
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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