Data-Driven Theoretical Design of Anion Cluster-Based Sodium Antiperovskite Superionic Conductors

Area of Science:

• Materials Science
• Solid-State Chemistry
• Computational Materials Design

Background:

• Sodium antiperovskite materials (APs) show promise as solid-state electrolytes due to their structural tolerance and formability.
• Limited experimental synthesis of APs necessitates exploration of new chemical spaces for improved ionic conductivity.

Purpose of the Study:

• To explore novel chemical spaces for sodium antiperovskite materials.
• To enhance thermal stability and sodium diffusivity in APs through strategic design.
• To identify APs with superior ionic conductivity for solid-state battery applications.

Main Methods:

• Utilized particle swarm optimization, high-throughput first-principles calculations, and ab initio molecular dynamics.
• Employed long time-scale machine-learning molecular dynamics simulations.
• Investigated strategies based on site-exchanging and anion clusters.

Main Results:

• Designed novel APs with simultaneously enhanced thermal stability and sodium diffusivity.
• Achieved a theoretical ionic conductivity of 39.05 mS/cm in Na3BrSO4 at room temperature.
• Demonstrated that coupled cluster rotation and sodium migration significantly boost ionic conductivity.

Conclusions:

• Site-exchanging strategies and anion clusters are effective for designing high-performance sodium antiperovskites.
• The coupling between anion rotation dynamics and cation migration is crucial for high ionic conductivity.
• The developed insights can guide the design of superionic conductors with cluster rotation dynamics.