Training a CNN model to predict the diffusivity of cations in nanoparticle-based electrolytes requires generating a large dataset of diverse nanoparticle topologies exhibiting a wide range of cation diffusivities. The dataset itself includes thousands of configurations of nanoparticles, represented in the form of 3D digitized images, and the values of the associated cation diffusivities, calculated using the mesoscale kMC simulations discussed in Section 2.2.