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Halide Superionic Conductors with Non-Close-Packed Anion Frameworks.

Jin-Da LuoYixi ZhangXiaobin ChengFeng LiHao-Yuan TanMei-Yu ZhouZi-Wei WangXu-Dong HaoYi-Chen YinBin JiangHong-Bin Yao
Published in: Angewandte Chemie (International ed. in English) (2024)
Halide superionic conductors (SICs) are drawing significant research attention for their potential applications in all-solid-state batteries. A key challenge in developing such SICs is to explore and design halide structural frameworks that enable rapid ion movement. In this work, we show that the close-packed anion frameworks shared by traditional halide ionic conductors face intrinsic limitations in fast ion conduction, regardless of structural regulation. Beyond the close-packed anion frameworks, we identify that the non-close-packed anion frameworks have great potential to achieve superionic conductivity. Notably, we unravel that the non-close-packed UCl 3 -type framework exhibit superionic conductivity for a diverse range of carrier ions, including Li + , Na + , K + , and Ag + , which are validated through both ab initio molecular dynamics simulations and experimental measurements. We elucidate that the remarkable ionic conductivity observed in the UCl 3 -type framework structure stems from its significantly more distorted site and larger diffusion channel than its close-packed counterparts. By employing the non-close-packed anion framework as the key feature for high-throughput computational screening, we also identify LiGaCl 3 as a promising candidate for halide SICs. These discoveries provide crucial insights for the exploration and design of novel halide SICs.
Keyphrases
  • solid state
  • ionic liquid
  • molecular dynamics simulations
  • high throughput
  • solar cells
  • perovskite solar cells
  • machine learning
  • quantum dots
  • single cell
  • deep learning
  • working memory
  • risk assessment