Solid-state batteries (SSBs) promise to meet the increasing demand for safe, high-power, and high-capacity energy storage. SSBs with solid electrolytes (SEs) offer potential advantages over conventional lithium-ion batteries with liquid electrolytes. Their performance, however, strongly depends on the structure and composition of the various interfaces contained in the different materials, which also change upon electrochemical cycling. We use Scanning transmission electron microscopy (STEM), to quantify properties of interfaces in battery materials. When compared to image simulations, the information on the sample structure and composition derived from STEM data can be quantitative. Combining STEM with a fast, pixelated detector allows for the acquisition of a full diffraction pattern at each scan point. From this, four-dimensional STEM (4D-STEM) datasets are available, which can be used to generate different data, e.g. annular dark field (ADF) as well as (annular) bright field ((A)BF) images, angular resolved STEM (ARSTEM) or differential phase contrast (DPC) data. With the example of cathode, anode and different SE materials for battery applications (e.g., NCM, Si, LLZO, LATP), we track the formation of different phases of and defects within the materials in dependence on synthesis as well as cycling conditions of the material and derive ABF as well as BF images from 4D datasets. These are used to also obtain difference images (ABF-BF). It will be shown that the composition of the materials and especially the Lithium content can be derived from the contrast of the different atomic columns in the structure. This is possible by comparing the experimental data sets to state of the art multi-slice simulations. This contribution will summarize the material science aspects of the energy materials investigated but also elucidate the potential of quantitative 4D-STEM to investigate materials.
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