4.8 Article

Dimensionality effect of conductive carbon fillers in LiNi1/3Mn1/3Co1/3O2 cathode

Journal

CARBON
Volume 188, Issue -, Pages 114-125

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.carbon.2021.11.014

Keywords

Lithium-ion battery; Single-walled carbon nanotubes; Morphological degradation; Chemical heterogeneity; Mosaic tomography; XANES tomography

Funding

  1. Center for Mesoscale Transport Properties, an Energy Frontier Research Center by the U.S. Department of Energy, Office of Science, Basic Energy Sciences [DE-SC0012673]
  2. DOE Office of Science by Brookhaven National Laboratory [DE-SC0012704]

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Modifying electrode materials and conductive fillers can enhance the performance and stability of electrodes. Three-dimensional quantification analysis of electrodes can provide a better understanding of the dimensionality effects of electrode materials.
Developing advanced electrode architectures through modifying active materials, conductive fillers, binders, and electrolytes as well as processing methods has drawn significant research interest. Due to the insufficient electrical conductivity of many active materials, adding conductive carbon fillers to composite electrodes provides the necessary electrical conductivity. The dimensionality effect among different conductive fillers has a significant impact on electrochemistry, which can be associated with morphological and chemical heterogeneities of electrodes. Here, synchrotron X-ray mosaic nanotomography and X-ray spectroscopy nanoimaging provided direct three-dimensional (3D) visualization and quantification capabilities to investigate the dimensionality effects of Super P (SP) and single-walled carbon nanotube (SWCNT) fillers on the capacity retention of LiNi1/3Mn1/3Co1/3O2 (NMC111). The results indicate that NMC/SWCNT electrodes, with a wrapping effect from the SWCNTs, exhibited more homogeneous particle size distributions, morphological changes, and chemical states than NMC/SP electrodes, without the wrapping effect. This work developed a framework of 3D quantification methods to study the capacity fading behavior associated with morphological and chemical heterogeneities and paved the way toward designing electrodes for high rate energy storage applications. (C) 2021 Published by Elsevier Ltd.

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