The success of the CNN model studied here for predicting cation diffusivity in nanocomposites with spherical nanoparticles clearly hinges on its ability to detect how nanoparticle positions and the related positional interparticle correlations influence diffusivity. Here, by modifying the types of microstructures we input into the revised CNN model, we aim to examine whether the CNN filters can adequately recognize and account for the impact of added or deleted nanoparticles, and accordingly predict the corresponding cation diffusivity.