Identifying Novel Lithium Superionic Conductors Using a High‐Throughput Screening Model Based on Structural Parameters

Abstract As the key component in solid‐state batteries, Li superionic conductors ought to exhibit high ionic conductivities (>10 −4 S cm −1 ) at room temperature ( σ RT ). However, identifying such materials is a grand challenge due to the limited number of known candidates and the difficulty of predicting σ RT with both efficiency and accuracy. Herein, a high‐throughput screening model is developed that requires only two easily accessible parameters: the diameter of Li‐ion diffusion path ( D path ) and the dimension of Li‐ion network ( D Li ). This model successfully identifies Li superionic conductors from 132 experimentally available Li‐ion conductors. Using this approach, 13 new candidates are screened out of the 21 686 Li‐containing materials from the Materials Project, and their Li superionic conductivity is confirmed by first‐principle molecular dynamics simulations. Notably, two N‐containing materials (i.e., Li 6.5 Ta 0.5 W 0.5 N 4 and Li 6.5 Nb 0.5 W 0.5 N 4 ) are identified, enriching the rare N‐based Li superionic conductor family, while Li 2 Mo 3 S 4 achieves the highest conductivity of 6.24 × 10 −2 S cm −1 due to its unique structure of interconnected Mo 6 O 8 clusters, providing a robust and optimal diffusion path. Li 6.5 Ta 0.5 W 0.5 N 4 , Li 6.5 Nb 0.5 W 0.5 N 4 , and Li 7 PSe 6 have been identified as promising solid‐state electrolytes for use at the anode interface for the solid‐state Li‐ion batteries, while Li 10 X(PS 6 ) 2 (X = Si, Ge, or Sn), Li 2 Mn 0.75 Ta 0.5 Sn 0.5 S 4 , and Li 2 Zn 0.5 TaS 4 are suitable for the cathode interface. This work not only proposes a highly effective and accurate screening model for exploring Li superionic conductors but also provides several new frameworks for designing systems with ultrahigh σ RT values.