Classification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers. (arXiv:2207.14114v1 [cond-mat.mtrl-sci])

FIB/SEM tomography represents an indispensable tool for the characterization
of three-dimensional nanostructures in battery research and many other fields.
However, contrast and 3D classification/reconstruction problems occur in many
cases, which strongly limits the applicability of the technique especially on
porous materials, like those used for electrode materials in batteries or fuel
cells. Distinguishing the different components like active Li storage particles
and carbon/binder materials is difficult and often prevents a reliable
quantitative analysis of image data, or may even lead …

arxiv classification classifiers images materials random sem