材料科学
超级电容器
多孔性
化学工程
储能
碳纤维
电化学
比表面积
多孔介质
纳米技术
调制(音乐)
电化学储能
功率密度
纳米孔
密度泛函理论
石墨
金属有机骨架
电解质
电流密度
作者
Jibi Kunjumon,Gurwinder Singh,Ajanya Maria Ruban,Harleen Kaur,Alan Larson,Ranjit Pati,Puspamitra Panigrahi,Davidson Sajan,Tung Tran,Antonio Tricoli,Sanje Mahasivam,Vipul Bansal,Ajayan Vinu
出处
期刊:Nano Energy
[Elsevier BV]
日期:2026-08-30
卷期号:158: 112362-112362
标识
DOI:10.1016/j.nanoen.2026.112362
摘要
The pore structure is a significant feature of porous carbons that accounts for their excellent performance in supercapacitors; however, the literature on pore modulation and cleansing is scarce. Here, a novel approach based on organic solvent-assisted pore modulation is reported to tune the pore hierarchy and local carbon-layer arrangement in porous carbons derived from waste biomass. The strategy involves adsorbing n-heptane into porous carbon at room temperature, thereby facilitating realignment of the carbon layers, improving pore hierarchy, and generating short-range graphitic domains. The solvent-assisted pore modulation, together with the high surface area and graphitization, led to a significant increase of 39.4% in specific capacitance, C sp (354 F g -1 /0.5 A g -1 ) as compared to bare porous carbon (254 F g -1 /0.5 A g -1 ). High energy and power densities of 6 Wh kg -1 /10 A g -1 and 13,500 W kg -1 /10 A g -1 , along with a C sp of 105.22 F g -1 /0.5 A g -1 , are achieved for a two-electrode supercapacitor. Density functional theory (DFT) calculations provided insights into an improved pore structure and solvent-induced modulation of the electronic structure, enhancing ion transport and charge storage. This straightforward and promising organic solvent-assisted pore-modulation strategy provides a new route to tailoring pore architecture and short-range graphitic ordering in porous carbons without high-temperature graphitization or chemical functionalization, thereby creating a potentially new line of research in these materials for advanced electrochemical energy-storage applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI