A more sophisticated approach was studied by combining a 3D physics-based modeling data with ML through the use of convolutional neural networks (CNNs) by Marcato et al. . In this work, a proof of concept of a time dependent discharge simulation of a 3D resolved microstructure was presented. This model was key to show that these ML surrogate models are not only capable of predicting battery metrics like voltage or current, but also are capable of unveiling the dynamics of the battery by showing the evolution of the lithiation on a three-dimensional structure.