In this study, we use long-timescale Machine Learning Molecular Dynamics (MLMD) to investigate the behaviour of the archetypal superionic conductor Li 3 N across the superionic transition. We characterise variations in diffusion, defect, and phonon properties between the normal and superionic regimes, and discuss the implications of these changes for ion transport in Li 3 N and other type-II superionic conductors.