The rapidly evolving field of inorganic solid-state electrolytes (ISSEs) has been driven in recent years by advances in data-mining techniques, which facilitates the high-throughput computational screening for candidate materials in the databases. The key to the mining process is the selection of critical features that underline the similarity of a material to an existing ISSE. Unfortunately, this selection is generally subjective and frequently under debate. Here we propose a subgraph isomorphism matching method that allows an objective evaluation of the similarity between two compounds according to the topology of the local atomic environment. The matching algorithm has been applied to discover four structure types that are highly analogous to the LiTi₂(PO₄)₃ NASICON prototype. We demonstrate that the local atomic environments similar to LiTi₂(PO₄)₃ endow these four structures with favorable Li diffusion tunnels and ionic conductivity on par with those of the prototype. By further taking into account the electronic structure and electrochemical stability window, 13 compounds are identified to be potential ISSEs. Our findings not only offer a promising approach toward rapid mining of fast ion conductors without limitation in the compositional range but also reveal insights into the design of ISSEs according to the topology of their framework structures.

中文翻译：

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通过子图同构匹配快速挖掘快离子导体


近年来，数据挖掘技术的进步推动了无机固态电解质（ISSE）领域的快速发展，这有助于对数据库中的候选材料进行高通量计算筛选。采矿过程的关键是选择强调材料与现有 ISSE 相似性的关键特征。不幸的是，这种选择通常是主观的，并且经常引起争议。在这里，我们提出了一种子图同构匹配方法，该方法允许根据局部原子环境的拓扑客观评估两个化合物之间的相似性。匹配算法已用于发现与 LiTi ₂ (PO ₄ ) ₃ NASICON 原型高度相似的四种结构类型。我们证明，类似于 LiTi ₂ (PO ₄ ) ₃ 的局域原子环境赋予这四种结构良好的 Li 扩散隧道和与这些结构相当的离子电导率原型的。通过进一步考虑电子结构和电化学稳定性窗口，13 种化合物被确定为潜在的 ISSE。我们的研究结果不仅为快速开采快离子导体提供了一种有前途的方法，不受成分范围的限制，而且还揭示了根据 ISSE 框架结构的拓扑结构对其设计的见解。