Discovery and Characterization of 1D materials via Data Mining and DFT
Joshua Paul and Richard Hennig
University of Florida, Material Science and Engineering, PO Box 116400, Gainesville FL, 32611
Two-dimensional (2D) materials have been of great interest since the discovery of free-standing graphene in 2004. One-dimensional (1D) materials present a complementary class of lowdimensional materials, which has not been received a lot of attention. Recently developed algorithms have been able to identify the dimensionality of structural motifs in bulk compounds materials based on bond networking, leading to the high-throughput discovery of 2D and 1D compounds in materials databases. In this work, we use the topological scaling algorithm to identify compounds with 1D structural motifs in the MaterialsProject database. Following, we characterize the isolated 1D chainlike structures using density-functional theory. We determine their formation energy relative to the bulk compound, magnetic moment, and electronic band structure. We predict several hundred sufficiently stable 1D materials with a broad range of properties, with 10% being metals and 46% having a net magnetic moment greater than .1 μB.