Although the data dispersion, especially in the 92 % AM samples, makes this method a rough estimation, we can see that the experimental and simulation data align very well. Experimental tortuosity factor sources always have a wide distribution due to the deviation from the considerations that the methodology requires, such as absolutely equal thicknesses, particle distributions and porosities for both electrodes in the symmetrical cell. In our case, the homogeneity of the 90 % samples were slightly better than those of the 92 %, resulting in a lower dispersion. Still, in all our cases it is well aligned with the tortuosity factor distributions and errors reported in literature for NMC cathodes. A more quantitative method to estimate the CBD internal porosity from the experimental data is the comparison between the fittings to the Bruggeman equation ( These two approaches lead to compatible final results, although the quantitative provides a univocal way to obtain the CBD internal porosity from experimental data. It is important to highlight that the methodology reported and developed in this work are, to the best of our knowledge, the first approach to obtain the equivalent CBD internal porosity from electrochemical experimental determinations. The importance of this value, as shown throughout this paper, can have a very significant influence on the tortuosity factor of the simulated microstructures. It should be noted that the morphology that the CBD acquires, as well as its internal porosity are expected to strongly depend on the manufacturing conditions as well as on the carbon additive selected. The strategy selected here is presented as an example case for the purposes of a proof of concept. In practice, the user should select the morphology better suited to their experimental conditions. Different tools for the generation of stochastic microstructures that allow different degrees of control of binder morphology are available, such as GeoDict or INNOV.