Data Mining for Three-Dimensional Organic Dirac Materials: Focus on Space Group 19

TL;DR

This paper uses group theory and data mining on an organic materials database to predict stable Dirac nodes in 3D organic crystals, identifying a specific space group conducive to Dirac node formation and analyzing six materials with potential for experimental observation.

Contribution

It introduces a novel combination of group theory and data mining to predict Dirac nodes in organic crystals, focusing on space group 19 and providing detailed analysis of synthesized materials.

Findings

Identified space group P2_12_12_1 as conducive to Dirac nodes.

Predicted two types of Dirac nodes: 8-fold and 4-fold degeneracies.

Found Dirac nodes near the Fermi surface in six organic materials.

Abstract

We combined the group theory and data mining approach within the Organic Materials Database that leads to the prediction of stable Dirac-point nodes within the electronic band structure of 3-dimensional organic crystals. We find a particular space group $P2_12_12_1$ ($\#19$) that is conducive to the Dirac nodes formation. We prove that nodes are a consequence of the orthorhombic crystal structure. Within the electronic band structure, two different kinds of nodes can be distinguished: 8-fold degenerate Dirac nodes protected by the crystalline symmetry and 4-fold degenerate Dirac nodes protected by band topology. Mining the Organic Materials Database, we present band structure calculations and symmetry analysis for 6 previously synthesized organic materials. In all these materials, the Dirac nodes are well separated within the energy and located near the Fermi surface, which opens up a possibility for their direct experimental observation.