超级电容器
生物量(生态学)
材料科学
碳纤维
储能
环境科学
工艺工程
纳米技术
化学
工程类
功率(物理)
复合材料
生态学
复合数
电化学
生物
电极
物理
物理化学
量子力学
作者
Jiashuai Wang,Xiao Zhang,Zhe Li,Yanqing Ma,Lei Ma
标识
DOI:10.1016/j.jpowsour.2020.227794
摘要
The carbon material based biomass in energy storage has attracted much interest due to their environmental friendly, natural abundance and special porous structures. In this paper, the relationship between the species of biomass-based electrode and properties of supercapacitors are systematically discussed. On the one hand, the influence of the specific morphologies, heteroatom-introducing and graphitization degree of active carbon on the electrochemical properties are analyzed in detail, which give a promising direction for biomass-based carbon in clean energy field. On the other hand, machine learning, especially artificial neural network model, has been widely used as data mining technology to predict the electrochemical properties of electrode materials. It makes the structure-performance relationship for biomass-based supercapacitors more specifically. Current development in synthesis of active carbon from biomass combined with theoretical prediction is summarized, which provides a meaningful guidance into the application of energy storage supercapacitors. Current challenges and new trends on the biomass-based carbon materials in supercapacitors have also been proposed.
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