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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 in cubic LLZO is limited by the low vacancy concentration. The hopping statistics also shows uncorrelated Poisson-like diffusion for Li in the cubic LLZO, and correlated diffusion for Li in the tetragonal LLZO in the temporal scale. Further analysis of the spatio-temporal correlation using site-to-site mutual information confirms the weak site dependence of Li diffusion in the cubic LLZO as the origin for the uncorrelated diffusion. This work puts forward a perspective on combining machine learning and information theory to interpret results of molecular dynamics simulations.

SUBMITTER: Chen C

PROVIDER: S-EPMC5240091 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Several "Beyond Li-Ion Battery" concepts such as all solid-state batteries and hybrid liquid/solid systems envision the use of a solid electrolyte to protect Li-metal anodes. These configurations are very attractive due to the possibility of exceptionally high energy densities and high (dis)charge rates, but they are far from being realized practically due to a number of issues including high interfacial resistance and difficulties associated with fabrication. One of the most promising solid electrolyte systems for these applications is Al or Ga stabilized Li7La3Zr2O12 (LLZO) based on high ionic conductivities and apparent stability against reduction by Li metal. Nevertheless, the fabrication of dense LLZO membranes with high ionic conductivity and low interfacial resistances remains challenging; it definitely requires a better understanding of the structural and electrochemical properties. In this study, the phase transition from garnet (Ia3̅d, No. 230) to "non-garnet" (I4̅3d, No. 220) space group as a function of composition and the different sintering behavior of Ga and Al stabilized LLZO are identified as important factors in determining the electrochemical properties. The phase transition was located at an Al:Ga substitution ratio of 0.05:0.15 and is accompanied by a significant lowering of the activation energy for Li-ion transport to 0.26 eV. The phase transition combined with microstructural changes concomitant with an increase of the Ga/Al ratio continuously improves the Li-ion conductivity from 2.6 × 10-4 S cm-1 to 1.2 × 10-3 S cm-1, which is close to the calculated maximum for garnet-type materials. The increase in Ga content is also associated with better densification and smaller grains and is accompanied by a change in the area specific resistance (ASR) from 78 to 24 Ω cm2, the lowest reported value for LLZO so far. These results illustrate that understanding the structure-properties relationships in this class of materials allows practical obstacles to its utilization to be readily overcome.

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

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Dataset Information

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

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OmicsDI is part of the ELIXIR infrastructure

Tweets

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