The microstructure of lithium‐ion battery electrodes determines their electrochemical performance and is strongly influenced by processing parameters. We present a virtual workflow that couples discrete element method (DEM) calendering, microstructure reconstruction, and electrode analysis to link cathode processing to structural properties. After validating this digital twin against a real cathode, we show the potential of our virtual workflow by conducting electrochemical simulations. First, our DEM‐calendering model proves to represent the calendering process accurately. Next, we reintegrate the carbon binder domain (CBD) into the compressed particle pack using five reconstruction schemes. For each reconstructed microstructure, we compute pore size distributions, tortuosities, effective diffusivities, and electronic conductivities. The CBD‐addition method that combines surface roughening of the active material with a realistic binder gradient within the electrode best reproduces experimentally measured transport properties. Lastly, we conduct electrochemical simulations across a range of C‐rates. These predict capacities that align well with those reported in literature, showing that our model can be used as the basis to detect diffusion‐limiting C‐rates. Overpotential analysis confirms that the Li‐ion transport, rather than electronic conduction, is the primary bottleneck. This suggests that microstructure optimization in terms of improving ionic pathways is necessary for improving this electrode's performance.
Ohnimus et al. (Fri,) studied this question.