Abstract The rapid development of the high-throughput calculations and materials genome approaches in recent years has improved researchers’ ability to design advanced materials. Crystal structure prediction techniques play an important role in high-throughput calculations and materials genome approaches. However, the huge computational cost of the widely used crystal structure prediction techniques based on the global optimization algorithms hinders the researchers from predicting the large or medium-sized crystal structures. In recent years, some metastable materials with excellent electrical, magnetic, optical and catalytic properties have attracted a lot of attention. However, there is currently a lack of a structure prediction technique with high energy resolution near the ground-state structures to meet the growing demands for the prediction of low-energy metastable materials. In this article, a set of easy-operation guidelines for constructing crystal structures is extracted from Pauling’s rules. Based on this set of guidelines, we have designed an algorithm called Pauling’s rules guided Monte Carlo search (PAMCARS), which predict the ground-state and meta-stable inorganic crystal structures of a given composition by combining a classical Monte Carlo search in the configuration space constrained by Pauling’s rules with ab initio structural relaxations. In the actual tests, the crystal structures of carbon allotropes, CaSO4, Ba2TiSi2O8 and BaAlBO3F2 are successfully predicted by this crystal structure prediction algorithm. In addition, a number of unreported high-symmetric metastable crystal structures of carbon, CaSO4 and Ba2TiSi2O8 are also predicted. The successful prediction of graphite layers indicates that PAMCARS is able to predict some layered materials assembled by the Van der Waals forces. Two of the predicted low-energy metastable crystal structures of Ba2TiSi2O8 may explain the property anomaly of Ba2TiSi2O8 around 160 °C. Pauling’s rules guided Monte Carlo search exhibits high efficiency and energy resolution in predicting the ground-state and metastable crystal structures in the tests.

中文翻译：

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鲍林规则指导蒙特卡罗搜索 (PAMCARS)：预测无机晶体结构的捷径

摘要 近年来，高通量计算和材料基因组方法的快速发展提高了研究人员设计先进材料的能力。晶体结构预测技术在高通量计算和材料基因组方法中发挥着重要作用。然而，广泛使用的基于全局优化算法的晶体结构预测技术的巨大计算成本阻碍了研究人员预测大中型晶体结构。近年来，一些具有优异电、磁、光和催化性能的亚稳态材料引起了广泛关注。然而，目前缺乏一种在基态结构附近具有高能量分辨率的结构预测技术来满足对低能亚稳态材料预测日益增长的需求。在本文中，从鲍林的规则中提取了一组用于构建晶体结构的简单操作指南。基于这组指南，我们设计了一种称为鲍林规则引导的蒙特卡罗搜索 (PAMCARS) 的算法，该算法通过在配置中结合经典的蒙特卡罗搜索来预测给定组合物的基态和亚稳态无机晶体结构空间受鲍林规则约束，具有从头算结构松弛。在实际测试中，碳同素异形体 CaSO4 的晶体结构，Ba2TiSi2O8 和 BaAlBO3F2 通过该晶体结构预测算法成功预测。此外，还预测了许多未报告的碳、CaSO4 和 Ba2TiSi2O8 的高对称亚稳态晶体结构。石墨层的成功预测表明PAMCARS能够预测一些由范德华力组装的层状材料。Ba2TiSi2O8 的两种预测的低能亚稳态晶体结构可以解释 Ba2TiSi2O8 在 160 °C 附近的性质异常。Pauling 的规则指导 Monte Carlo 搜索在预测测试中的基态和亚稳态晶体结构方面表现出高效率和能量分辨率。石墨层的成功预测表明PAMCARS能够预测一些由范德华力组装的层状材料。Ba2TiSi2O8 的两种预测的低能亚稳态晶体结构可以解释 Ba2TiSi2O8 在 160 °C 附近的性质异常。Pauling 的规则指导 Monte Carlo 搜索在预测测试中的基态和亚稳态晶体结构方面表现出高效率和能量分辨率。石墨层的成功预测表明PAMCARS能够预测一些由范德华力组装的层状材料。Ba2TiSi2O8 的两种预测的低能亚稳态晶体结构可以解释 Ba2TiSi2O8 在 160 °C 附近的性质异常。Pauling 的规则指导 Monte Carlo 搜索在预测测试中的基态和亚稳态晶体结构方面表现出高效率和能量分辨率。