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.