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无机电子化合物是一类电子被局域在阳离子晶格骨架中的特殊材料，在电极材料、电子发射、催化等领域的应用前景广阔。近年来，发现和设计新型电子化合物成为研究热点之一。然而，当前主流方法均采用“直接”策略，难以有效识别和发现结构复杂的电子化合物前驱体。本工作提出了一种新颖的“间接”策略——不是直接得到电子化合物而是以其前驱体为导向的筛选策略。首次基于美国矿物学家晶体结构数据库(AMCSD)，设计了一个结合拓扑模式识别与第一性原理计算的多阶段筛选流程。该流程的核心是定义了一种基于化学局部配位环境的拓扑描述符，用以精准捕捉潜在的电子化合物前驱体结构。基于对AMCSD数据库中20 488个矿物晶体结构的系统性筛选，确定了18个有高潜力的候选材料。从这些材料中不仅识别了已被实验报道的方钠石和磷灰石型电子化合物(验证了本方法的有效性)，而且还发现了7种全新未见报道的结构原型。本工作不仅展示了“间接”策略在筛选和发现新型电子化合物上的有效性，同时也证实了矿物数据库是未被充分开发的电子化合物材料宝库，所建立的模式筛选方法也为系统性发掘其他新型功能材料提供了普适性参考方案。
Abstract：Introduction Inorganic electrides, characterized by localized electrons acting as anions within the cationic lattice framework, represent a unique and emerging class of materials with significant potential for applications in electrode materials, electronics, catalysis, and beyond. Despite their promise, the discovery of new electrides, especially those with complex structures, remains a formidable challenge. Current computational approaches, which predominantly employ "direct" strategies to screen for ideal electrides, often fail to identify promising candidates that could be derived from stable precursor compounds through anion removal. Recognizing that an electride is fundamentally a reduced derivative of its electron-saturated precursor, we introduce an innovative "indirect" screening strategy. This novel approach centers on identifying potential precursor materials that can be transformed into electrides, rather than directly searching for the final electride structures themselves. Consequently, this work endeavors to unlock the vast, yet underexplored, potential of mineral databases as a treasure trove for such precursor systems and to establish a robust, generalizable methodology for their efficient identification and discovery. Methods We proposed a comprehensive four-stage screening workflow, leveraging the American Mineralogist Crystal Structure Database(AMCSD) to systematically identify potential electride precursors. The initial phase involved the pre-processing of 20 488 mineral structures to standardize the dataset, ensuring uniformity and consistency. Subsequently, a preliminary screening stage was implemented, imposing constraints on compositional complexity, unit cell size, and explicitly excluding specific systems such as carbonates and metal oxides to narrow down the candidate pool. The cornerstone of our approach was the pattern screening stage, which utilized a novel topological descriptor. This descriptor was specifically engineered to identify local coordination environments where a removable anion(X = O, F, Cl, Br, I) is coordinated by 4 to 6 identical metal cations(the XMn motif). This stage effectively filtered out structures that did not meet the predefined criteria for potential electride formation. In the final stage, the candidate structures identified through pattern screening were subjected to a rigorous fine screening process based on density functional theory(DFT). This involved structural optimization of both the precursor compounds and their corresponding anion-removed derivatives. Following optimization, electronic structure calculations were performed to assess the band gap transition and the spatial localization of electrons using the electron localization function(ELF). Specific thresholds were applied to identify the most promising electride precursors from this refined pool of candidates. Results and discussion The proposed four-stage screening strategy demonstrated remarkable efficiency, successfully narrowing down from an initial dataset of 20 488 mineral structures to a final selection of 18 high-potential electride precursors. DFT calculations provided conclusive electronic evidence for their electride character: all identified precursors were wide-gap insulators(band gap > 2.0 e V), and upon removal of the central anion(X = O, F, Cl, Br, I), all underwent a characteristic electronic transition. This transition is characterized by the formation of new in-gap states at the Fermi level following anion removal. Specifically, 13 systems transitioned to metallic states, while 5 became narrow-gap semiconductors(< 0.5 e V). ELF analysis unambiguously confirmed the spatial localization of the resulting excess electrons within the anion vacancy sites. The effectiveness of our strategy was further validated by the identification of experimentally known sodalite-and apatite-type electrides among the candidates. Beyond merely validating the method, the discovery of 7 previously unreported structural prototypes underscores the strategy's power for novel discovery. This outcome not only highlights the rich diversity of electride precursors within mineral databases but also demonstrates the generalizability of our topological descriptor for identifying the essential chemical motif required for electride formation. Conclusions In conclusion, we have successfully established a robust and innovative screening strategy that is based on an indirect approach. This strategy has proven to be highly effective in identifying 18 high-potential inorganic electride precursors from an initial dataset of 20 488 mineral structures. The indirect strategy's success is underscored by its remarkable ability to not only reproduce known sodalite-and apatite-type electrides but also, more significantly, to uncover 7 previously unreported structural prototypes. The comprehensive spectrum of electron localization dimensionalities(0D, 1D, 2D) observed across the entire candidate pool further highlights the broad applicability and generalizability of our methodology. This work establishes mineral databases as a rich and valuable resource for the discovery of novel electrides. It also illustrates the power and potential of precursor-targeted screening in uncovering new materials. The generalizable framework presented here offers a versatile and powerful tool that can be extended to the systematic discovery of other functional materials based on specific local coordination patterns. The identified candidates provide a solid foundation for future experimental synthesis and in-depth investigation, paving the way for further advancements in the field of materials science.
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基本信息:
DOI：10.14062/j.issn.0454-5648.20250812
中图分类号:O611;TP311.13
引用信息:
[1]袁晓泽,周余伟,张香玉,等.矿物数据库中新型无机电子化合物材料的模式筛选与发现[J].硅酸盐学报,2026,54(01):25-34.DOI:10.14062/j.issn.0454-5648.20250812.
基金信息:
国家自然科学基金资助项目（22225206,52401299）; 北京市科技计划课题（Z181100005118014）
2025-11-06
2025
2026-01-04
2026
2
2026-01-07
2026-01-07
2026-01-07