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The Effect of Microstructure On Transport Properties of Porous Electrodes.

机译:微观结构对多孔电极输运性能的影响。

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摘要

The goal of this work is to further understand the relationships between porous electrode microstructure and mass transport properties. This understanding allows us to predict and improve cell performance from fundamental principles. The investigated battery systems are the widely used rechargeable Li-ion battery and the non-rechargeable alkaline battery. This work includes three main contributions in the battery field listed below.;Direct Measurement of Effective Electronic Transport in Porous Li-ion Electrodes. An accurate assessment of the electronic conductivity of electrodes is necessary for understanding and optimizing battery performance. The bulk electronic conductivity of porous LiCoO2-based cathodes was measured as a function of porosity, pressure, carbon fraction, and the presence of an electrolyte. The measurements were performed by delamination of thin-film electrodes from their aluminum current collectors and by use of a four-line probe.;Imaging and Correlating Microstructure To Conductivity. Transport properties of porous electrodes are strongly related to microstructure. An experimental 3D microstructure is needed not only for computation of direct transport properties, but also for a detailed electrode microstructure characterization. This work utilized X-ray tomography and focused ion beam (FIB)/scanning electron microscopy (SEM) to obtain the 3D structures of alkaline battery cathodes. FIB/SEM has the advantage of detecting carbon additives; thus, it was the main tomography tool employed. Additionally, protocols and techniques for acquiring, processing and segmenting series of FIB/SEM images were developed as part of this work. FIB/SEM images were also used to correlate electrodes' microstructure to their respective conductivities for both Li-ion and alkaline batteries.;Electrode Microstructure Metrics and the 3D Stochastic Grid Model. A detailed characterization of microstructure was conducted in this work, including characterization of the volume fraction, nearest neighbor probability, domain size distribution, shape factor, and Fourier transform coefficient. These metrics are compared between 2D FIB/SEM, 3D FIB/SEM and X-ray structures. Among those metrics, the first three metrics are used as a basis for SG model parameterization. The 3D stochastic grid (SG) model is based on Monte Carlo techniques, in which a small set of fundamental inter-domain parameters are used to generate structures. This allows us to predict electrode microstructure and its effects on both electronic and ionic properties.
机译:这项工作的目的是进一步了解多孔电极微观结构和质量传输特性之间的关系。这种理解使我们能够根据基本原理来预测和改善电池性能。研究的电池系统是广泛使用的可充电锂离子电池和不可充电碱性电池。这项工作包括以下列出的电池领域的三个主要贡献:多孔锂离子电极中有效电子传输的直接测量。为了理解和优化电池性能,必须对电极的电导率进行准确评估。测量了基于多孔LiCoO 2的阴极的整体电子电导率,其与孔隙率,压力,碳分数和电解质的存在有关。测量是通过将薄膜电极从铝集电器上分层并使用四线探针进行的。将微结构成像并与电导率相关。多孔电极的传输性能与微观结构密切相关。实验3D微观结构不仅需要用于直接传输特性的计算,而且还需要详细的电极微观结构表征。这项工作利用X射线断层扫描和聚焦离子束(FIB)/扫描电子显微镜(SEM)来获得碱性电池阴极的3D结构。 FIB / SEM具有检测碳添加剂的优势;因此,它是使用的主要层析成像工具。此外,这项工作还开发了用于获取,处理和分割FIB / SEM图像系列的协议和技术。 FIB / SEM图像还用于将锂离子电池和碱性电池的电极微结构与其各自的电导率相关联。电极微结构度量和3D随机网格模型。在这项工作中进行了详细的微观结构表征,包括体积分数,最近邻概率,畴尺寸分布,形状因子和傅立叶变换系数的表征。将这些指标在2D FIB / SEM,3D FIB / SEM和X射线结构之间进行比较。在这些指标中,前三个指标用作SG模型参数化的基础。 3D随机网格(SG)模型基于蒙特卡洛技术,其中一小部分基本域间参数用于生成结构。这使我们能够预测电极的微观结构及其对电子和离子性质的影响。

著录项

  • 作者

    Peterson, Serena W.;

  • 作者单位

    Brigham Young University.;

  • 授予单位 Brigham Young University.;
  • 学科 Energy.;Chemical engineering.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 216 p.
  • 总页数 216
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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