Automated geometry characterization of laser-structured battery electrodes

Abstract

Micro structuring of battery electrodes with pulsed laser radiation substantially increases the performance of lithium-ion batteries. For process design and monitoring, determining the resulting hole diameters and depths is essential. This study presents an automated, model-based approach for the geometry characterization of laser-drilled structures in battery electrodes. An iteratively re-weighted least squares algorithm is used for fitting of a reference plane to confocal laser scanning microscopy images of laser-structured electrodes. Using a threshold-based segregation of the generated weights, the holes are segmented from the pristine electrode surfaces. The results from the automated geometry determination were found to coincide well with manual measurements. By reducing the image resolution, the runtime of the code could be decreased, which yet lowered the accuracy of the hole depth prediction. In a sensitivity analysis, the algorithm performed stably under changes in the recording conditions, such as altered image brightness, frame rate, or vertical resolution. In conclusion, the presented method reduces the effort and increases the reproducibility for analyzing large experimental data sets in laser electrode structuring. Furthermore, the approach can be successfully transferred to other applications, which is demonstrated by indentations in battery current collector foils stemming from electrode calendering.