Data mining of molecular dynamics data reveals Li diffusion characteristics in garnet Li₇La₃Zr₂O₁₂.

ABSTRACT: Understanding Li diffusion in solid conductors is essential for the next generation Li batteries. Here we show that density-based clustering of the trajectories computed using molecular dynamics simulations helps elucidate the Li diffusion mechanism within the Li₇La₃Zr₂O₁₂ (LLZO) crystal lattice. This unsupervised learning method recognizes lattice sites, is able to give the site type, and can identify Li hopping events. Results show that, while the cubic LLZO has a much higher hopping rate compared to its tetragonal counterpart, most of the Li hops in the cubic LLZO do not contribute to the diffusivity due to the dominance of back-and-forth type jumps. The hopping analysis and local Li configuration statistics give evidence that Li diffusivity i

SUBMITTER: Chen C 

PROVIDER: S-EPMC5240091 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature