European Journal of Chemistry

Toward an improved solid-state Li electrolyte: A first-principles investigation of the structure, Li-ion migration pathways, and ionic conductivity of Li7La3Zr2O12

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Muhammad Mozammal Kamal Raju
Yulun Han
Dmitri Kilin
Yi Ding
Qifeng Zhang

Abstract

Among solid state electrolytes, garnet-type Li7La3Zr2O12 (LLZO) has attracted considerable attention due to its high electrochemical stability, safety, and compatibility with lithium metal anodes. However, its lithium-ion conductivity strongly depends on the crystal structure: the tetragonal phase exhibits a significantly lower ionic conductivity than the cubic phase. In this work, first-principles density functional theory (DFT) and ab initio molecular dynamics (AIMD) are employed to systematically investigate the crystallographic structure, lithium-ion migration pathways, and ionic conductivity of both tetragonal and cubic LLZO. Lithium ion trajectories were analysed to determine diffusion coefficients over a wide temperature range. Activation energies are extracted from Arrhenius behaviour, and room-temperature ionic conductivities are extrapolated from high-temperature simulations. The results reveal that cubic LLZO possesses an intrinsically disordered lithium sublattice with abundant vacant sites and shorter migration pathways, which significantly enhance lithium-ion mobility. Consequently, the extrapolated room temperature ionic conductivity of cubic LLZO reaches the order of ~10-3 S/cm, in good agreement with experimental reports, while tetragonal LLZO exhibits much lower conductivity. This study provides atomistic-level insight into lithium diffusion mechanisms in LLZO and offers guidance for designing high-performance garnet-type solid electrolytes through structural disorder and vacancy engineering.


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Raju, M. M. K.; Han, Y.; Kilin, D.; Ding, Y.; Zhang, Q. Toward an Improved Solid-State Li Electrolyte: A First-Principles Investigation of the Structure, Li-Ion Migration Pathways, and Ionic Conductivity of Li7La3Zr2O12. Eur. J. Chem. 2026, 17, 125-137.

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Supporting Agencies

The National Science Foundation CHE-1944921, The US Army Combat Capabilities Development Command (DEVCOM) Ground Vehicle Systems Center (GVSC) and the National Center for Manufacturing Sciences (MCMS) (No. 2021021-142041, No. 2023167-142245), The Center for Computationally Assisted Science and Technology (CCAST) at North Dakota State University (National Science Foundation Major Research Instrumentation (MRI) Award No. 2019077).
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