Using Topology to Predict Electrides in the Solid State.

Area of Science:

• Solid-state chemistry and materials science
• Computational materials discovery
• Quantum mechanics and electron density topology

Background:

• Electrides are materials characterized by electron density localized in interstitial sites, lacking direct interatomic bonding.
• The rigorous definition of electrides relies on quantum mechanical topological criteria, specifically the presence of non-nuclear attractors (NNAs).

Purpose of the Study:

• To accelerate the discovery of crystalline electrides under various pressure conditions.
• To employ topological criteria and evolutionary algorithms for identifying novel electride candidates.

Main Methods:

• Utilized crystal structure prediction methods, specifically the XtalOpt evolutionary algorithm.
• Integrated topological descriptors, focusing on the localization and quantification of non-nuclear attractors (NNAs), as a primary discriminator for electride character.
• Conducted a comprehensive crystal structure prediction study of Ca5Pb3 at 20 GPa.

Main Results:

• Successfully demonstrated the reliability of the combined approach for predicting and sorting electride phases.
• Identified several previously unknown low-enthalpy phases possessing NNAs in interstitial sites.
• Discovered a new P4/mmm electride structure.

Conclusions:

• Evolutionary algorithms guided by rigorous topological descriptors are effective for surveying complex material phases.
• The developed strategy can reliably identify new electride candidates, advancing the field of materials discovery.