Quantitative microstructural analysis of lithium-ion battery cathodes

In this application note, ZESS discusses the quantitative microstructure analysis of lithium-ion batteries using ZEN Intellesis. Two different segmentation methods: classic thresholding and machine learning-based were evaluated and compared against reference measurements using a laboratory balance. A detailed description of the fundamental functionality of the machine learning-based approach is given, and this approach has the potential to provide more accurate segmentation results due to its robustness against image variations.