A materials informatics approach to the identification of one-band correlated materials analogous to the cuprates

TL;DR

This paper introduces a materials informatics method to identify new one-band correlated materials similar to cuprates, leading to the discovery of five promising compounds with strong correlation physics.

Contribution

The study develops a data-driven approach using materials informatics to find and verify new one-band correlated materials analogous to cuprates.

Findings

Identified five candidate compounds with one-band electronic structures.

Demonstrated strong correlation effects including Mott insulating behavior.

Validated candidates with density functional theory calculations.

Abstract

One important yet exceedingly rare property of the cuprate high-temperature superconductors is the presence of a single correlated $d$ band in the low-energy spectrum, leading to the one-band Hubbard model as the minimal description. In order to search for materials with interesting strong correlation physics as well as possible benchmark systems for the one-band Hubbard model, here we present a new approach to find one-band correlated materials analogous to the cuprates by leveraging the emerging area of materials informatics. Using the composition, structure, and formation energy of more than half a million real and hypothetical inorganic crystalline materials in the Open Quantum Materials Database, we search for synthesizable materials whose nominal transition metal $d$ electron count and crystal field are compatible with achieving an isolated half-filled $d$ band. Five Cu compounds, including bromide, oxide, selenate, and pyrophosphate chemistries, are shown to successfully achieve the one-band electronic structure based on density functional theory band structure calculations. Further calculations including magnetism and explicit on-site Coulomb interaction reveal significant evidence for strong correlation physics in the five candidates, including Mott insulating behavior and antiferromagnetism. The success of our data-driven approach to discovering new correlated materials opens up new avenues to design and discover materials with rare electronic properties.