Journal
NPJ COMPUTATIONAL MATERIALS
Volume 7, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41524-021-00681-8
Keywords
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Funding
- U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344]
- U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, through the Battery Materials Research program - Laboratory Directed Research and Development Program at LLNL [15-ERD-022, 18-FS-019]
- LLNL Institutional Computing Grand Challenge program
- National Science Foundation [DMR-1710630, DMR180033]
- Donald W. Hamer Foundation through a Hamer Professorship
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This study demonstrates an efficient and general computational method for predicting effective ionic conductivity of complex polycrystalline oxide-based solid electrolytes, revealing the interdependence between atomistic and mesoscopic impacts on ionic conductivity. The results offer fundamental understanding of the physical origins of variability in ionic conductivities and practical design guidance for achieving desired ionic transport properties.
Although multiple oxide-based solid electrolyte materials with intrinsically high ionic conductivities have emerged, practical processing and synthesis routes introduce grain boundaries and other interfaces that can perturb primary conduction channels. To directly probe these effects, we demonstrate an efficient and general mesoscopic computational method capable of predicting effective ionic conductivity through a complex polycrystalline oxide-based solid electrolyte microstructure without relying on simplified equivalent circuit description. We parameterize the framework for Li7-xLa3Zr2O12 (LLZO) garnet solid electrolyte by combining synthetic microstructures from phase-field simulations with diffusivities from molecular dynamics simulations of ordered and disordered systems. Systematically designed simulations reveal an interdependence between atomistic and mesoscopic microstructural impacts on the effective ionic conductivity of polycrystalline LLZO, quantified by newly defined metrics that characterize the complex ionic transport mechanism. Our results provide fundamental understanding of the physical origins of the reported variability in ionic conductivities based on an extensive analysis of literature data, while simultaneously outlining practical design guidance for achieving desired ionic transport properties based on conditions for which sensitivity to microstructural features is highest. Additional implications of our results are discussed, including a possible connection between ion conduction behavior and dendrite formation.
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