We believe that the speed and accuracy of the presented physics-informed DL model paves the way towards optimization loops of the electrode microstructure, by accounting explicitly for the 3D microstructural features (dealing to electrochemical and transport heterogeneities upon the electrode functioning) and not on the average properties of such electrodes as in our previous works. As shown in this work, our model can understand and predict the dynamics of the calendering process. Moreover, we consider that our model has tremendous potential to growth in several aspects such as accuracy and predictability. Therefore, our incoming efforts will be focused on continuing the development of the model and test it for other formulations and in other manufacturing stages.