Using Topology to Predict Electrides in the Solid State

TL;DR

This paper introduces a topological approach combined with evolutionary algorithms to efficiently predict and discover new electride materials in the solid state by analyzing electron density features.

Contribution

It presents a novel method integrating topological electron density criteria with crystal structure prediction to identify electrides, demonstrated through a case study on Ca5Pb3.

Findings

Successfully predicted new electride phases including P4/mmm structure.

Validated the approach by identifying NNAs as reliable electride indicators.

Enhanced discovery efficiency for electride materials using topological descriptors.

Abstract

Electrides are characterized by electron density highly localized in interstitial sites, which do not coincide with the interatomic contacts. The rigorous quantum mechanical definition of electrides is based upon topological criteria derived from the electron density, and in particular the presence of non-nuclear attractors (NNAs). We employ these topological criteria in combination with crystal structure prediction methods (the XtalOpt evolutionary algorithm), to accelerate the discovery of crystalline electrides at ambient and non-ambient pressures. The localization and quantification of NNAs is used as the primary discriminator for the electride character of a solid within a multi-objective evolutionary structure search. We demonstrate the reliability of this approach through a comprehensive crystal structure prediction study of Ca5Pb3 at 20 GPa, a system previously theorized to exhibit electride character under compression. Our strategy could predict, and sort on-the-fly, several unknown low-enthalpy phases that possess NNAs in interstitial loci, such as the newly discovered P4/mmm structure. These results demonstrate how evolutionary algorithms, guided by rigorous topological descriptors, can be relied upon to effectively survey complex phases to find new electride candidates.