Parametric stochastic 3D microstructure models have proven to be a powerful tool to describe the microstructure of battery electrodes [1,2,3]. While these models exhibit a remarkably good structural fit to tomographic image data of real electrodes, there is still a challenge to overcome regarding their applicability for virtual materials design, i.e., to go away from the fitted specifications of the model and systematically change the morphology, such that virtual, but realistic microstructures can be generated and analyzed with respect to their functional properties . In order to do so, the number of model parameters should be as small as possible, and they should be directly related to morphological characteristics. Recently, we developed a framework for such a microstructure generator . In this framework, model parameters directly describe morphological properties. To give an example, the size distribution and volume fraction of active particles can be directly adjusted. Furthermore, we show that our modelling framework can realistically describe tomographic image data of a wide spectrum of real battery electrodes, and how it can be used to generate virtual electrode microstructures with different porosities, particle size distributions and more advanced structural design concepts like, e.g., multi-layer electrodes . Several examples of simulated electrode microstructures can be found in Figure 1.
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