In this study, we demonstrate the above strategy by the application of deep learning approaches for predicting the diffusion coefficient of cations in single-ion conducting nanoparticle-based electrolytes. The choice of the system was inspired by a recent study of ours probing the mechanistic bases for ion transport observations reported in these electrolytes. Our results in such a context were consistent with the reported experimental behavior of electrolytes comprising silica nanoparticles, cofunctionalized with polyethylene glycol ligands and tethered anionic species coupled to Li + ions, dispersed in ion-conducting tetraglyme solvent. Our simulation results suggested that ionic conductivity in such systems is primarily controlled by cation diffusion along functionalized nanoparticle surfaces.