Nano-porous materials can be imaged spatially by focused ion beam scanning electron microscopy (FIB-SEM). This method generates a stack of SEM images that has to be segmented (or reconstructed) to serve as basis for structural characterization. To this end, we apply two state-of-the-art algorithms. We study the influence of the original image’s voxel size on estimates of morphological characteristics and effective permeabilities. Special attention is paid to analyzing anisotropies due to the FIB-SEM typical anisotropic sampling. Quantitative comparison of morphological descriptors and flow properties of reconstructed data is enabled by the use of synthetic FIB-SEM sets for which a ground truth is available. Moreover, in that case, reconstruction parameters can be chosen optimally, too.

纳米多孔材料可通过聚焦离子束扫描电子显微镜（FIB-SEM）在空间上成像。该方法生成一堆SEM图像，必须对其进行分割（或重建）以用作结构表征的基础。为此，我们应用了两种最先进的算法。我们研究了原始图像的体素大小对形态特征和有效磁导率估计的影响。由于FIB-SEM典型的各向异性采样，因此特别要注意分析各向异性。通过使用合成FIB-SEM集合，可以对形态描述子和重建数据的流动特性进行定量比较，而这些合成FIB-SEM集合具有可利用的基础。此外，在这种情况下，也可以最佳地选择重建参数。