Using first-principles calculations, we studied the structural, energetic, and electrochemical properties of Li x C 6 system. Comparing to the PBE functionals and previously reported ab initio results, the rVV10 functional accurately reproduces the experimental lattice parameters, phase stability, and voltage curve of the Li x C 6 system. By implementing an active learning approach to sam-ple additional Li x C 6 structures and label them with the rVV10 functional, we developed an accurate and stable QRNN model for molecular dynamics simulations of the Li x C 6 system. By carrying out large scale MD simulations, we investigated Li diffusion in Li x C 6 structures as a function of stage, Li content and temperature. We found a non-monotonic trend between D and x, with three pronounced minima, where the Li x C 6 structures undergo the phase transitions between different stages. The decrease of D near phase transition can be attributed to a decrease of fast diffusion Li ions. The phase transition dependent Li diffusion agrees well with previous experimental and theoretical results, demonstrating the capability of our QRNN model in unraveling the complex relation between Li diffusion and phase transition in a graphite anode. In addition, one rational approach to mitigate the phase transition induced Li diffusion bottleneck could be introducing porous structures in graphite which provides multichannel Li diffusion. Recently, Inamoto et al. reported that the Li diffusivity in the graphite structures with pores formed in the graphene is orders of magnitude higher than that of pristine graphite structures.