High-throughput first-principle prediction of collinear magnetic topological materials

Abstract

The success of topological band theory and symmetry-based topological classification significantly advances our understanding of the Berry phase. Based on the critical concept of topological obstruction, efficient theoretical frameworks, including topological quantum chemistry and symmetry indicator theory, were developed, making a massive characterization of real materials possible. However, the classification of magnetic materials often involves the complexity of their unknown magnetic structures, which are often hard to know from experiments, thus, hindering the topological classification. In this paper, we design a high-throughput workflow to classify magnetic topological materials by automating the search for collinear magnetic structures and the characterization of their topological natures. We computed 1049 chosen transition-metal compounds (TMCs) without oxygen and identified 64 topological insulators and 53 semimetals, which become 73 and 26 when U correction is further considered. Due to the lack of magnetic structure information from experiments, our high-throughput predictions provide insightful reference results and make the step toward a complete diagnosis of magnetic topological materials.

Pressure-dependent multiplet-excitation energies of α-Al2O3:Cr3+ by the first-principles method

“…3) First-principle calculations are expected to provide a way to solve such problems, as in the case of other studies of the computational materials designs (CMD). [4][5][6][7][8][9] However, it is not so easy to predict the luminescent properties in the first-principles method. This is because we have to treat multiplets which can be described by the superpositions of Slater determinants.…”