Searching for electronically two dimensional metals in high-throughput ab initio databases

Computational Materials Science(2020)

引用 1|浏览23
暂无评分
摘要
Due to the high degree of improvement and prediction success of ab initio calculations, the advance in Materials Science has been partially shifted from the empirical chemical quest of new compounds to the systematic calculation of putative structures that can yield compounds with promising properties. In particular, two dimensional (2D) materials are at present a central target, as many potential devices rely on particular characteristics of a single layer of atoms or low dimensional electronic active sheets in bulk materials. Several works have focused on this paradigm, yielding a large list of new interesting 2D candidates. Here, we introduce a technique based on an algorithmic filter for searching prospective candidates in very large electronic structure databases. It is designed to detect electronic bands with low energy dispersion along particular directions in reciprocal space, i.e. those perpendicular to certain plane or surface. We propose it as an absolute criterion for obtaining all possible two dimensional compounds. With it we show that previous explorations have missed out a whole group of possible two dimensional materials, namely only electronically 2D.
更多
查看译文
关键词
2D,Two dimensional materials,HTc superconductors,Machine learning,Data mining,High throughput materials discovery,Electronic structure,Fermi surface,Fermiology
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要