Further improvements in material development and production technology are required to reduce production costs and increase the capacity of Li-ion batteries. The electrode production is one of the most crucial production steps. The electrodes consist of aluminum or copper foils coated with a slurry on both sides. The slurry consists of active materials, a binder phase, conduction additives and a solvent or water. The solvent or water is removed by a drying step after the coating. After drying the electrodes are compressed to reduce pore volume and increase the capacity (see Figure 1). Every single production step can influence the microstructure of the electrodes. This microstructure has an important influence on the performance of the battery cell. The aim is an electrode that maintains a good electrical conductivity, sufficient ionic conductivity through a continuous pore network and a high mechanical stability over the whole lifetime. The particle morphology, particle size, distribution and particle shape of the active materials play an important role in the cycling behavior of Li-ion batteries [1]. A homogeneous distribution of the active material in the electrodes is essential for homogenous distribution of lithium inside the electrodes. This correlates with a homogenous current distribution, which is favorable for a good utilization of active material and long lifetime [2-5].

Reliable tools for the investigation and characterization of the electrode microstructure are necessary to increase the understanding of the influence of different production steps and parameters on the microstructure. For this purpose, we use a combination of microscopy images and machine learning algorithms. Conventional sample mounting, polishing and ion milling were used for sample preparation of cathode foils. High-resolution scanning electron microscopy images visualize the distribution of the active materials within the electrode coating. We use machine-learning (ML) approaches to segment the active material of the cathode foils. Further measurements are performed to get information of the local distribution of active material inside the cathode coating (compare Figure 2). Using this approach, we can visualize the evolution of the microstructure during electrode compression. We can identify local deviations in the distribution of active material in the electrode coating and near the coating edge. These investigations can be used for process development or for the evaluation of the production quality.

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