Project Description:

Batteries are a vital component of many daily life devices and electric vehicles. Their performance depends heavily on the microstructure of the electrodes. While huge progress has been made to increase energy density, a full picture of the responsible microstructure is still lacking. FIB-SEM is a powerful tool that allows the investigation of 2D images of these materials. However, low contrast between the raw materials, high computational requirements, and the need for image analysis and interpretation slow the adoption of this technique as a standard measurement procedure.

This project aims to develop a standardized workflow for the analysis of complex battery materials via FIB-SEM segmentation and reconstruction. This workflow is used to create a database containing microstructural metrics and their impact on the material performance. Both are used to support quantum-based analysis methods for a more efficient and reliable analysis of FIB-SEM data. The successful candidate will work in an interdisciplinary consortium of other research institutions and companies.

At the INM – Leibniz Institute for New Materials, commercial and self-designed battery materials will be used to analyze their microstructure. Promising methods for increasing contrast will be explored and evaluated to produce images of the highest possible quality. Segmentation and reconstruction methods will be applied and compared to novel quantum-based approaches.

Your Tasks:

• Prepare electrode materials using established
• Characterize the microstructure of electrode materials using FIB-
• Apply and develop 2D segmentation and 3D reconstruction
• Explore different methods to increase contrast between light
• Correlate structure–property relationships using microstructural
• Develop mechanistic concepts of composite conductivity based on your
• Publishing results in peer-reviewed journals and presentations at
• Supervise and support graduate and undergraduate