Nanoscale/microscale porous graphene-like sheets derived from different tissues and components of cane stalk for high-performance supercapacitors
Source abstract
Abstract
Different biomass components have different effects on the microstructures and physicochemical properties of biocarbons. And the properties of biocarbons still need to be further improved. Nanoscale/microscale graphene-like sheets are synthesized with KOH as micropore-forming agent, Fe(NO3)3⋅9H2O as mesopore-forming agent and graphite catalyst. It is systematically researched to get the effects of biomass components on them. Cane sugar can form flat graphene-like nanosheets with high conductivity. Their performance drops sharply at 100A g−1 , indicating that biocarbons need a support of carbon skeleton to operate normally at high current density. Bagasse pith contains amount of cellulose and hemicellulose, which are good for forming pores. Bagasse pith-derived graphene-like sheets possess large specific surface area ( 2923.58m2g−1 ), high specific capacitance ( 514.14F g−1 at 0.3A g−1 and 372.57F g−1 at 100A g−1 ) and high energy density. Due to homogeneous coated doping with graphene-like nanosheets, sugarcane pith-derived graphene-like sheets possess low impedance ( Rs=0.02Ω ), high rate capability (maintained 82.34% from 0.3 to 100A g−1 ) and high cycling stability (maintained 101.51% after 5000 cycles), which is better than lots of graphene doping. Sugarcane skin contains more lignin which has hexagonal carbon rings. The graphitization extent of sugarcane skin-derived graphene-like sheets is significantly high. The results provide references to select carbon precursors, and show a novel graphene-like doping method which is suitable for different materials and various fields.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Supercapacitor Materials and Fabrication · Electrospun Nanofibers in Biomedical Applications · Advancements in Battery Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (67)
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