Technological advances, e.g., of consumer electronics and electric cars, continuously increase the different requirements batteries have to fulfil. This led to the development of many different cell chemistries, optimized for specific applications. For next-generation batteries, one approach is to use organic polymers as active electrode materials. Those polymer-based batteries have potentially higher power densities and a smaller ecological footprint, compared to classical Li-ion batteries. Different classes of polymers have shown promising results, despite of some drawbacks, such as a limited lifetime or a high self-discharge.
It is well-known that the microstructure of electrodes is a key factor for the performance of battery cells. Thus, the 3D microstructure of differently manufactured electrodes for polymer-based batter-ies with, e.g., varying binder-additive compositions and/or volume fraction of active material, is inves-tigated by combining tomographic 3D imaging with statistical image analysis. In particular, synchro-tron tomography is used to resolve the 3D microstructure consisting of redox-active polymer, binder-conducting additive phase with carbon material and pores. This allows for the computation of mor-phological characteristics that are experimentally not accessible. In this talk, we focus on the local heterogeneity of volume fractions of the constituents, specific surface area of the poly-mer phase and the length of shortest transportation paths through both, polymer and binder-additive phase. The performed statistical analysis helps to get insights into the influence of the manufacturing process on the electrode microstructure and, thus, on the performance of the cell.