The Role of Delocalized Chemical Bonding in Square-Net-Based Topological Semimetals

Principles that predict
reactions or properties of materials define
the discipline of chemistry. In this work, we derive chemical rules,
based on atomic distances and chemical bond character, which predict
topological materials in compounds that feature the structural motif
of a square-net. Using these rules, we identify over 300 potential
new topological materials. We show that simple chemical heuristics
can be a powerful tool to characterize topological matter. In contrast
to previous database-driven materials’ categorization, our
approach allows us to identify candidates that are alloys, solid-solutions,
or compounds with statistical vacancies. While previous material searches
relied on density functional theory, our approach is not limited by
this method and could also be used to discover magnetic and statistically
disordered topological semimetals.