The existing design principles and screening strategies of superionic conductors predominantly focus on the perspective of a static crystal structure. However, the dynamic mechanism involving anion rotational motion as well as its interaction with cation translational motion has received less exploration, especially in the realm of the accelerated discovery of new fast ionic conductors with these strong dynamic couplings. Herein, we design a multistep density functional theory molecular dynamics (DFT-MD) high-throughput workflow based on the structural feature of an isolated framework to rapidly screen Na superionic conductors with polyanion rotation. Interpretable machine-learning classification indicates that structures with larger atomic volumes and smaller polyanions tend to exhibit anion rotational behavior. Building on the observation of persistent, large-angle anion reorientation and the time-spatial correlation of Na hops and polyanion rotations, we identified polyanion rotation behavior for the first time in 10 new compounds and quantified the contribution of polyanion rotation to Na diffusion, among which three are novel Na superionic conductors with significant cation–anion dynamics coupling, including NaGaBr₄, NaNbCl₆, and Na₄SiSe₄. Additionally, we developed highly accurate moment tensor potentials for NaNbCl₆ and Na₄SiSe₄. Long time scale machine-learning molecular dynamics simulations (MLMD) at 300 K revealed that the anion rotation still exists in NaNbCl₆ at room temperature, while Na₄SiSe₄ displays non-Arrhenius behavior. This study provides valuable guidance for the development of new fast ion conductors utilizing polyanion rotation.

中文翻译：

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在钠超离子导体中收获聚阴离子旋转？

现有的超离子导体的设计原理和筛选策略主要集中在静态晶体结构的角度。然而，涉及阴离子旋转运动及其与阳离子平移运动相互作用的动力学机制得到的探索较少，特别是在加速发现具有这些强动态耦合的新型快离子导体领域。在此，我们基于孤立框架的结构特征设计了多步密度泛函理论分子动力学（DFT-MD）高通量工作流程，以快速筛选具有聚阴离子旋转的Na超离子导体。可解释的机器学习分类表明，具有较大原子体积和较小聚阴离子的结构往往表现出阴离子旋转行为。基于对持续大角度阴离子重新定向的观察以及 Na 跃点和聚阴离子旋转的时空相关性，我们首次在 10 种新化合物中确定了聚阴离子旋转行为，并量化了聚阴离子旋转对 Na 扩散的贡献，其中这三种是具有显着阳离子-阴离子动力学耦合的新型Na超离子导体，包括NaGaBr ₄、NaNbCl ₆和Na ₄ SiSe ₄。此外，我们还开发了 NaNbCl ₆和 Na ₄ SiSe ₄的高精度矩张量势。 300 K 下的长时间尺度机器学习分子动力学模拟 (MLMD) 表明，室温下NaNbCl _{6中阴离子旋转仍然存在，而 Na 4} SiSe ₄表现出非阿累尼乌斯行为。这项研究为利用聚阴离子旋转开发新型快离子导体提供了宝贵的指导。