In the present work, cation diffusion coefficients computed for the microstructures in the training dataset using kMC simulations parameterized with a fixed set of cation local diffusivities and cation-nanoparticle affinities, determined from the coarse-grained MD simulations of our previous study, serve as the ground truth labels. To emphasize the efficacy of employing the combination of CNN model and topology optimization algorithm to identify non-intuitive microstructures with high diffusivities, we define a dimensionless number,