In the past few years, tomography has emerged as an indispensable tool to characterize and quantify the microstructural parameters of porous media, including lithium ion battery electrodes and separators, fuel cell parts, and supercapacitor electrodes, as well as electrolysis diaphragms. However, tomographic data often suffer from low image contrast between the pore space and the solid phase. As a result, data binarization is error-prone, which translates into uncertainties in the calculated parameters, such as porosity, tortuosity, or specific surface area. We systematically investigate this error propagation on a set of seven commercial negative lithium ion battery electrodes imaged with X-ray tomographic microscopy, and find that, for low porosity electrodes, the selection of binarization criteria can lead to uncertainties in the calculated tortuosity exceeding a factor of two. Our analysis shows that Otsu's interclass variance, which can be determined from a simple and computationally cheap analysis of the histogram of gray values, is a good predictive indicator of the expected uncertainty in the microstructural characteristics.

中文翻译：

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确定从断层扫描数据中提取的微结构参数的不确定性† ‡

在过去的几年中，层析成像已经成为表征和量化多孔介质的微观结构参数的必不可少的工具，包括锂离子电池电极和隔板，燃料电池部件，超级电容器电极以及电解隔膜。然而，层析数据经常遭受孔隙空间与固相之间图像对比度低的困扰。结果，数据二值化容易出错，这转化为计算参数的不确定性，例如孔隙率，曲折度或比表面积。我们系统地研究了在用X射线断层显微镜观察的七个商用锂离子电池负极上的误差传播情况，发现对于低孔隙率的电极，选择二值化标准可能导致所计算出的曲折度的不确定性超过两倍。我们的分析表明，可以通过对灰度值的直方图进行简单且计算便宜的分析来确定的Otsu类间方差，是预测微结构特征不确定性的良好预测指标。