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近年来，二维材料的研究非常热门。制备二维材料可以用剥离法，即从块体的层状材料中剥离出单层二维材料，比如从石墨中剥离出石墨烯。为了获得更多的新型二维材料，可以利用高通量计算从材料数据库中筛选出容易剥离的层状材料。层状结构筛选中的一个关键步骤是判断材料中是否存在二维结构，因此需要高效准确的维度判断算法。目前常用的维度判断算法在处理某些复杂结构时会得到错误的结果。例如对于自穿插结构，已有的算法会低估它们的维度。
南京大学物理学院孙建教授团队系统地阐述了如何利用晶体商图这一理论工具分析晶体网络、计算其维度。他们发现通过晶体商图，还可以计算晶体网络穿插多重度。作者比较了不同的晶体维度判断算法，分析了自穿插结构对维度判断结果的影响，解释了穿插多重度计算方法的原理。他们用基于商图的方法在大型材料数据库中筛选出了数百个具有不同维度和多重度的复杂结构，发现最复杂的结构的多重度高达11。并进一步研究了筛选出来的结构的性质，发现其中一些自穿插结构具有较高气体吸附能力和多样的电子结构，可能在气体存储、选择性催化或光催化等领域有潜在应用价值。该研究有助于更全面、准确地运用高通量方法，筛选包括低维材料在内的特定晶体结构材料。该文近期发表于npj Computational Materials 6: 143 (2020)，英文标题与摘要如下，点击左下角“阅读原文”可以自由获取论文PDF。
Determining dimensionalities and multiplicities of crystal nets
Hao Gao, Junjie Wang, Zhaopeng Guo & Jian Sun
Low-dimensional materials have attracted significant attentions over the past decade. To discover new low-dimensional materials, high-throughput screening methods for structures with target dimensionality have been applied in different materials databases. For this purpose, the reliability of dimensionality identification is therefore highly important. In this work, we find that the existence of self-penetrating nets may lead to incorrect results by previous methods. In stead of this, we use the quotient graph to analyse the topologies of structures and compute their dimensionalities. Based on the quotient graph, we can calculate not only the dimensionality but also the multiplicity of self-penetrating structures. As a demonstration, we screened the Crystallography Open Database using the method and find hundreds of structures with different dimensionalities and high multiplicities up to eleven. Some of the self-penetrating materials may have application values in gas storage, selective catalysis or photocatalysis because of their high gas sorption capacities and various electronic structures.
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