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Unraveling the Potassium Storage Performance of Carbon Nanosheets Derived from Heavy Oils

ZHAO Qing-shan LIU Qin-lian LI Yi-wen JI Tian YAO Yu-yue ZHAO Yi-kun DENG Wei HU Han WU Ming-bo

赵青山, 刘钦莲, 李义文, 姬甜, 姚雨悦, 赵屹坤, 邓炜, 胡涵, 吴明铂. 揭示重质油衍生碳纳米片的储钾性能. 新型炭材料(中英文). doi: 10.1016/S1872-5805(24)60875-9
引用本文: 赵青山, 刘钦莲, 李义文, 姬甜, 姚雨悦, 赵屹坤, 邓炜, 胡涵, 吴明铂. 揭示重质油衍生碳纳米片的储钾性能. 新型炭材料(中英文). doi: 10.1016/S1872-5805(24)60875-9
ZHAO Qing-shan, LIU Qin-lian, LI Yi-wen, JI Tian, YAO Yu-yue, ZHAO Yi-kun, DENG Wei, HU Han, WU Ming-bo. Unraveling the Potassium Storage Performance of Carbon Nanosheets Derived from Heavy Oils. New Carbon Mater.. doi: 10.1016/S1872-5805(24)60875-9
Citation: ZHAO Qing-shan, LIU Qin-lian, LI Yi-wen, JI Tian, YAO Yu-yue, ZHAO Yi-kun, DENG Wei, HU Han, WU Ming-bo. Unraveling the Potassium Storage Performance of Carbon Nanosheets Derived from Heavy Oils. New Carbon Mater.. doi: 10.1016/S1872-5805(24)60875-9

揭示重质油衍生碳纳米片的储钾性能

doi: 10.1016/S1872-5805(24)60875-9
基金项目: 国家自然科学基金(22208375、22138013);山东省泰山学者项目(ts201712020);中国“万人计划”科技领军人才项目(W03020508)
详细信息
    通讯作者:

    赵青山. E-mail:qszhao@upc.edu.cn

    吴明铂. E-mail:wumb@upc.edu.cn

Unraveling the Potassium Storage Performance of Carbon Nanosheets Derived from Heavy Oils

Funds: This work is financially supported by the National Natural Science Foundation of China (No. 22208375, 22138013), China; the financial support from Taishan Scholar Project of Shandong Province of China (No. ts201712020), China. Technological Leading Scholar of 10000 Talent Project (No. W03020508), China
More Information
  • 摘要: 作为石油炼制过程的副产品,重质油具有含碳量高、成本低、可调性强等特点,是构建钾离子电池电极材料极具竞争力的前驱体。然而,重质油组分组成与其电化学储钾性能之间的关系仍不明确。本研究选用具有不同组分组成的重质油(催化裂化油浆、石油沥青和脱油沥青)作为碳源,通过熔盐法制备了三种碳纳米片作为钾离子电池负极材料。研究结果表明,重质油的四组分组成会导致不同的片层厚度、sp3-C/sp2-C比率和缺陷水平,进而对其储钾性能产生重要的影响。其中,催化裂化油浆芳香烃含量高、重组分含量适中,衍生的碳纳米片(CNS-FCCs)具有更小的片层厚度、更大的层间距(0.372 nm)和更多的褶皱缺陷,这些结构特征有助于促进电荷/离子的传输扩散,增加储钾位点并促进反应动力学。CNS-FCCs作为钾离子电池负极材料具有出色的K+存储能力(在0.1 A g−1下循环100次后比容量为248.7 mAh g−1)、长循环寿命(在1.0 A g−1下循环800次后比容量为190.8 mAh g−1)和优异的倍率性能,在报道的碳材料中位于前列。本研究揭示了重质油组分对碳材料结构及其电化学性能之间的影响机理,对设计和开发高效的重质油衍生钾离子电池碳基电极材料具有指导意义。
  • Figure  1.  (a) Schematic illustration of the preparation process of CNS, and (b) the four-component composition of the three heavy oils

    Figure  2.  SEM images of (a) CNS-FCCs, (b) CNS-PA, and (c) CNS-DOA. TEM and HRTEM images of (d, g) CNS-FCCs, (e, h) CNS-PA, and (f, i) CNS-DOA. The insets illustrate the interlayer spacing of the three samples

    Figure  3.  (a) XRD patterns, (b) Raman spectra, and (c) XPS survey spectra of CNS-FCCs, CNS-PA and CNS-DOA. C 1s XPS spectra of (d) CNS-FCCs, (e) CNS-PA, and (f) CNS-DOA

    Figure  4.  (a) CV curves for the first three cycles at a scanning rate of 0.1 mV s−1 and (b) charge-discharge curves of CNS-FCCs at 0.1 A g−1. (c) Cycle performances at 0.1 A g−1, (d) long-cycling performances at 1 A g−1, (e) rate performances at different current densities of CNS-FCCs, CNS-PA, and CNS-DOA. (f) The first cycle charge-discharge curves of CNS-FCCs from 0.1 to 5.0 A g−1

    Figure  5.  (a) EIS curves, (b) GITT curves, K+ diffusion coefficients during (c) charging and (d) discharging processes of CNS-FCCs, CNS-PA, and CNS-DOA

    Figure  6.  (a) CV curves of CNS-FCCs from 0.2 to 1.4 mV s−1, (b) b values, (c) pseudocapacitive contributions at various scan rates, and (d) pseudocapacitive contribution (shaded region) at 1.4 mV s−1 of CNS-FCCs

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  • 收稿日期:  2024-05-03
  • 录用日期:  2024-07-01
  • 修回日期:  2024-06-30
  • 网络出版日期:  2024-07-02

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