Design of sodium superionic conductors based on multiple crystal structure prediction methods

Abstract

All-solid-state sodium-ion batteries (ASSSIBs) represent a promising next-generation battery technology offering advantages of low cost and high safety. In ASSSIBs, sodium superionic conductors (SICs) are commonly employed as solid-state electrolytes (SSEs) facilitating rapid Na-ion transport. Sulfide sodium SICs with Cl-ions have attracted much attention for their high ionic conductivity and structural stability. Therefore, the exploration of additional sulfide sodium SICs containing Cl-ions is of significant importance. In this work, we have integrated two crystal structure prediction methods, i.e., the data mining structure prediction (DMSP) algorithm and the crystal structure analysis by particle swarm optimization (CALYPSO) code, to explore the Na–P–S–Cl quaternary system. Two promising sodium SICs were identified: Na6PS5Cl (NPSC1) with space group P213 and Na5PS4Cl2 (NPSC2) with space group Amm2. First-principles calculations were used to evaluate the potential of the two novel sodium SICs as SSEs. NPSC1 is a completely novel structure that demonstrated a room-temperature conductivity (σRT) of 0.67 mS cm−1, which is one order of magnitude higher than that of the known Na6PS5Cl (Cc or Pna21 space group). In contrast, NPSC2 derived from an existing structure through element substitution exhibited a σRT of 0.23 mS cm−1. Both sodium SICs exhibit three-dimensional diffusion pathways. NPSC1 and NPSC2 also show better electrode compatibility than other sulfides and they rapidly form a passivation layer on contact with the electrode. Furthermore, the electronic conductivity of both structures is poor, which is a prerequisite for a sodium SIC to be used as a SSE. This study not only identifies two potential sodium SIC materials but also demonstrates the significant potential of integrating diverse crystal structure prediction methods, providing innovative concepts for the rational design of novel sodium SIC materials.

Graphical abstract: Design of sodium superionic conductors based on multiple crystal structure prediction methods

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Article information

Article type
Paper
Submitted
01 Mar 2025
Accepted
22 Apr 2025
First published
09 May 2025

Phys. Chem. Chem. Phys., 2025, Advance Article

Design of sodium superionic conductors based on multiple crystal structure prediction methods

X. Zhan, Z. Ren, J. Zhang, S. Zou, H. Yuan, J. Luo, Y. Liu, J. Nai, P. Shi, Y. Wang and X. Tao, Phys. Chem. Chem. Phys., 2025, Advance Article , DOI: 10.1039/D5CP00812C

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