Lithium ion batteries consist of three main porous components: anode, cathode, and in between them the separator, an electronically isolating membrane. Structural details of the constituent materials and their electrochemical mechanisms during battery operation cover several length scales, from the nanometer to the millimeter range. Grasping the full complexity of the multi-length scale processes and capturing an entirely realistic description of a lithium ion battery system is not only essential for a better understanding of battery physics, but also for the rational selection of materials, manufacturing processes and operational parameters. Therefore, understanding the relationship between the materials’ structure and their physico-chemical properties along with all involved and interacting physical phenomena is crucial. An investigation of the interplay between geometrical and material effects and their influence on battery performance requires an accurate representation of the structure, with clearly identified materials. Chapter 1 provides a general overview of physical interactions in lithium ion batteries covering the relevant length scales and linking them to the components’ microstructure. We summarize experimental imaging and scattering methods used to gather the 3D structural information, and discuss the involved data processing and analysis. Furthermore, examples for multiphysics modelling and simulations on battery microstructures, used to study the complex problems in LIBs, are presented. This thesis focuses on two of the aforementioned components comprising a lithium ion battery: the separator and a silicon-graphite composite anode. A crucial step in the lithium ion battery manufacturing process is infilling the porous structure with liquid electrolyte. We use the electrochemically inert separator as a model system to investigate the influence of structure on the electrolyte wetting behavior. Poor wetting is known to contribute to residual gas in the battery, causing poor performance. To investigate this process, we introduce the theory of incomplete wetting in Chapter 2. By performing quasi-static simulations on a 3D structure of a polyethylene separator, the influence of the 3D structure on the amount of gas entrapped in the pore space is highlighted. We demonstrate, that incomplete wetting can explain the discrepancy between theoretically predicted and experimentally measured transport coefficients. We also show that quasi-static wetting models overestimate the amount of residual gas in the membranes. The dynamics of the electrolyte-gas flow in the pores are considered in Chapter 3, where we use a ceramic-coated separator, imaged by focused ion beam – scanning electron microscopy (FIB-SEM) tomography and segmented into four phases (pore, polymer, binder, and ceramic particles) to do so. The imbibition behavior of this multilayer structure is investigated by dynamic pore network modeling. This allows us to track the moving wetting front and shows which structural features lead to gas entrapments. Upon electrochemical cycling, battery electrodes change their microstructure leading to increased ionic and electric resistance and accelviii erated cell degradation. In this thesis, we image and segment silicongraphite anodes to analyze their microstructural behavior. Herby, we particularly focus on changes of the carbon black-binder domain upon cycling. The nanometer-sized carbon black-binder domain ensures electrical contact and mechanical stability between the micrometer-sized active particles, graphite and silicon; its detachment leads to capacity fade. A multiphase segmentation of the anode poses challenges due to a tradeoff in resolution, field of view and image acquisition time, as well as low contrast between the graphite particles and the pore space. To overcome these challenges, in Chapter 4, a neural network is trained on real and artificially generated electrode structures and used to segment twelve samples imaged by transmission x-ray tomographic microscopy. The structural changes upon cycling of these silicon-graphite composite anode samples are then analyzed. We show the different distributions of the carbon black-binder domain in the vicinity of graphite and silicon active particles. This is important not only for the computational generation of such electrode structures, but also for a better understanding of degradation mechanisms in silicon-graphite composite anodes. Understanding multiphysics problems in lithium ion batteries not only poses a challenge to measurement techniques. Imaging techniques rely on modeling and analysis to understand the measured data. Chapter 5 summarizes the findings of this thesis and presents an outlook on novel approaches for data analysis involving machine learning and data augmentation.