High-entropy materials shift the traditional materials discovery paradigm to one that leverages disorder, enabling access to unique chemistries unreachable through enthalpy alone. A MRSEC team has developed a high-throughput framework for discovering and understanding the single-phase formation of high-entropy oxides (HEOs) by integrating computation and experiment in a self-consistent feedback loop. To more rapidly explore rock salt composition space, the team utilizes CHGNet machine-learning interatomic potentials with impressive accuracy even in disordered systems.

Two computational descriptors resolve the single-phase stability for all eight equimolar rock salt HEO compositions explored to date and lead to the discovery of a novel non-equimolar rock salt HEO containing Ca. This collaborative workflow workflow is currently being applied to explore more complex crystal structures that may possess emerging property opportunities.