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首页> 外文会议>Charging amp; infrastructure symposium 2018 >Nanoscale Imaging, Quantification, and Modeling of Mechanical Degradation in Lithium-Ion Batteries
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Nanoscale Imaging, Quantification, and Modeling of Mechanical Degradation in Lithium-Ion Batteries

机译：锂离子电池中机械降解的纳米级成像，量化和建模

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摘要

For lithium ion batteries, graphite remains the anode material or choice due to its low cost, mechanical robustness, and electrochemical properties. Because of that, graphite electrodes are subject to microstructural optimization and compositional progression with the goal to improve the electrochemical performance upon operation and to increase the specific capacity. In our work, we statistically characterize the microstructure of different commercial graphite electrodes by means of particle size distribution, surface area, porosity, tortuosity, and transport properties. X-ray tomography enables the reconstruction of 3D representations of the microstructure. We quantify the inhomogeneity of the graphite electrodes and relate it to their electrochemical behavior using simulations on the reconstructions of the real microstructures. The simulation results imply that inhomogeneous structures exhibit higher local overpotentials, which not only decrease the reversible capacity but also make inhomogeneous microstructures more prone to the development of onsets of lithium plating upon graphite lithiation. Producing homogeneous electrodes pays off in greater safety and higher reversible capacity [1]. Another approach to improve graphite based lithium ion battery electrodes is the fabrication of graphite-silicon composite anodes. Silicon and silicon-graphite based electrodes hold great promise as next generation negative electrodes for lithium ion batteries due to their high specific capacity. However, detachment of the electrically connecting carbon black-binder domain from the silicon active material upon electrochemical operation is a major degradation issue in these materials, leading to loss of active material and rapid capacity fade of the battery. These phenomena are hard to investigate using X-ray or electron imaging techniques as the electrode constituents graphite, carbon black, silicon and the electrolyte filled pore space all consist of light elements that show weak image contrast among each other. In our work, we show how to overcome these imaging challenges using a combination of staining techniques. We are able to differentiate between all phases in the electrode at different length scales and to investigate the nano-scale deformation of the carbon black binder domain upon electrochemical cycling [2]. Furthermore, we are capable of tracking volumetric changes in the microstructures using digital volume correlation techniques to map out the distribution of electrochemical activity in an operational cell [3].
机译：对于锂离子电池，石墨因其低成本，机械坚固性和电化学性能而仍然是负极材料或选择。因此，对石墨电极进行微结构优化和成分发展，目的是改善操作时的电化学性能并提高比容量。在我们的工作中，我们通过粒度分布，表面积，孔隙率，曲折度和传输特性，从统计学上表征了不同商品化石墨电极的微观结构。 X射线断层扫描可以重建微观结构的3D表示。我们对石墨电极的不均匀性进行量化，并使用对真实微观结构重建的模拟将其与它们的电化学行为联系起来。仿真结果表明，不均匀的结构表现出较高的局部超电势，这不仅降低了可逆容量，而且使不均匀的微观结构更易于在石墨锂化时发生锂镀层的开始发展。生产均匀的电极可以提高安全性和可逆容量[1]。改进基于石墨的锂离子电池电极的另一种方法是制造石墨-硅复合阳极。硅和硅石墨基电极因其高比容量而作为下一代锂离子电池负极具有广阔的前景。然而，在电化学操作时，电连接的炭黑-粘合剂域与硅活性材料的分离是这些材料中的主要降解问题，导致活性材料的损失和电池的快速容量衰减。使用X射线或电子成像技术很难对这些现象进行研究，因为电极成分石墨，炭黑，硅和电解质填充的孔隙空间均由彼此显示较弱图像对比度的轻元素组成。在我们的工作中，我们展示了如何通过结合使用染色技术来克服这些成像挑战。我们能够区分电极中不同长度尺度的所有相，并研究电化学循环后炭黑粘合剂域的纳米尺度变形[2]。此外，我们能够使用数字体积相关技术追踪微结构中的体积变化，以绘制出可操作电池中电化学活性的分布图[3]。

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  • 来源
  • 会议地点 Mainz(DE)
  • 作者

    Simon Mueller; Patrick Pietsch; Ben-Elias Brandt; Paul Baade; Jens Eller; Martin Ebner; Chris Burns; Daniel Westhoff; Julian Feinauer; Vincent De Andrade; Federica Marone; Marco Stampanoni; Jeff Dahn; Vol Schmidt; Francesco De Carlo; Vanessa Wood;

  • 作者单位

    ETH Zurich, Laboratory tor Nanoelectronics, Department or Information Technology and Electrical Engineering, Zurich, CH-8092 Switzerland;

    ETH Zurich, Laboratory tor Nanoelectronics, Department or Information Technology and Electrical Engineering, Zurich, CH-8092 Switzerland;

    ETH Zurich, Laboratory tor Nanoelectronics, Department or Information Technology and Electrical Engineering, Zurich, CH-8092 Switzerland;

    ETH Zurich, Laboratory tor Nanoelectronics, Department or Information Technology and Electrical Engineering, Zurich, CH-8092 Switzerland;

    ETH Zurich, Laboratory tor Nanoelectronics, Department or Information Technology and Electrical Engineering, Zurich, CH-8092 Switzerland;

    ETH Zurich, Laboratory tor Nanoelectronics, Department or Information Technology and Electrical Engineering, Zurich, CH-8092 Switzerland;

    Dalhousie University, Department of Physics and Atmospheric Science, Halifax, NS Canada;

    Ulm University, Institute of Stochastics, Ulm, Germany;

    Ulm University, Institute of Stochastics, Ulm, Germany;

    Argonne National Laboratory, Advanced Photon Source, Lemont, IL USA;

    Swiss Light Source, Paul Scherrer Institut, Villigen, Switzerland;

    Swiss Light Source, Paul Scherrer Institut, Villigen, Switzerland,Institute for Biomedical Engineering of the University and ETH Zurich, Zurich, Switzerland;

    Dalhousie University, Department of Physics and Atmospheric Science, Halifax, NS Canada;

    Ulm University, Institute of Stochastics, Ulm, Germany;

    Argonne National Laboratory, Advanced Photon Source, Lemont, IL USA;

    ETH Zurich, Laboratory tor Nanoelectronics, Department or Information Technology and Electrical Engineering, Zurich, CH-8092 Switzerland;

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