Phase instability-coupled fracture behavior in garnet LLZO solid electrolytes: a machine learning-enabled atomistic study
Key Points
The research examines how phase instability affects fracture behavior in LLZO solid electrolytes.
Utilized machine learning techniques to analyze atomistic simulations.
Studied the mechanical properties of garnet-type solid electrolytes under various conditions.
Investigated the relationship between phase instability and fracture mechanisms.
Identified key fracture mechanisms linked to phase instabilities.
Demonstrated that phase changes significantly impact the integrity of LLZO solid electrolytes.
Found that machine learning can effectively predict fracture behavior under different scenarios.
Abstract
Fracture in the garnet-type solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) poses a critical threat to both the performance and safety of solid-state batteries.