We analyze the effect of the hyperparameter 𝑛 𝐷𝐸𝑀 , which is the number of DEM steps performed between two DL predictions. We evaluate the accuracy of the dried electrode microstructure predictions by calculating different electrode functional metrics. Furthermore, the model has been tested in a different formulation than the one used as training data, showing outstanding results in terms of the accuracy of the electrode functional metrics. Finally, we compare the computational cost of both approaches, PAML vs. pure DEM.