Dr. Ingo Manke
HZB für Materialien und Energie
Dr. Ingo Manke
Image: Dr. Ingo Manke
About the Speaker
Dr. Ingo Manke is a physicist and the Head of the Imaging Group within the Institute of Applied Materials at the Helmholtz-Zentrum Berlin (HZB). With a career spanning over two decades, he has established himself as a leading international expert in the field of operando imaging and digital twins for energy materials. His research primarily utilizes advanced X-ray and neutron tomography to visualize the internal 3D/4D microstructures of batteries and fuel cells, specifically focusing on degradation mechanisms like dendrite formation and water transport. A highly cited author with hundreds of publications, Dr. Manke plays a pivotal role in bridging experimental physics and materials science at the BESSY II synchrotron, where his work directly informs the development of safer, more efficient next-generation energy storage and conversion technologies.
Abstract
Three-Dimensional Morphology of Polymer-based Batteries: Combining Tomographic 3D Imaging with Modeling and Simulation
The 3D morphology of battery electrodes is a crucial factor for their performance and degradation behavior. Ensuring simultaneous ionic and electronic conductivity requires an optimal hierarchical 3D structure on the micro- and nanometer scales. Therefore, accurate knowledge of this morphology is indispensable to improve polymer-based batteries.
This talk provides an overview of recent developments in the analysis, modeling, and simulation of polymer-based battery electrode materials to better understand their structure-property-fabrication relationships. Advanced imaging techniques, such as FIB/SEM and synchrotron X-ray tomography, are used for detailed multiscale analysis. A main challenge is separating the 3D distribution of different materials within the complex mixture of redox-active polymers, conductive carbon, and binders. Through AI-supported statistical 3D image analysis, correlations between fabrication parameters and transport-relevant morphological descriptors of pristine and aged electrodes are quantified. This information feeds into spatially resolved numerical transport simulations using a multiscale electrochemical model. Finally, some results on the creation of virtual 3D morphologies by Generative AI will be demonstrated. This enables the systematic, cost-effective study of electrode microstructures (Virtual Materials Testing and Design).
Altogether, combining 3D imaging with model-based simulation generates design recommendations to optimize the electrochemical performance of polymer-based battery electrodes.
Fig.1: Tomographies of polymer-based battery electrodes
Picture: HZB, University of Ulm, University of Jena