Accelerated Inorganic Electrides Discovery by Generative Models and Hierarchical Screening

TL;DR

This paper introduces a rapid discovery framework combining generative models and hierarchical screening to identify new electrides with exceptional electronic properties from large chemical spaces.

Contribution

It presents a novel accelerated discovery method integrating physical principles, generative modeling, and hierarchical screening to find electrides efficiently.

Findings

Identified 264 new electron-rich compounds, including 13 stable electrides.

Explored over 8,000 chemical compositions with high-throughput DFT validation.

Demonstrated a generalizable approach for targeted materials discovery.

Abstract

Electrides are exotic compounds in which excess electrons occupy interstitial regions of the crystal lattice and serve as anions, exhibiting exceptional properties such as low work function, high electron mobility, and strong catalytic activity. Although they show promise for diverse applications, identifying new electrides remains challenging due to the difficulty of achieving energetically favorable electron localization in crystal cavities. Here, we present an accelerated materials discovery framework that combines physical principles, diffusion-based materials generation with hierarchical thermodynamic and electronic structure screening. Using this workflow, we systematically explored 1,510 binary and 6,654 ternary chemical compositions containing excess valence electrons from electropositive alkaline, alkaline-earth, and early transition metals, and then filtered them with a high throughput validation on both thermodynamical stability and electronic structure analysis. As a result, we have identified 264 new electron rich compounds within 0.05 eV/atom above the convex hull at the density functional theory (DFT) level, including 13 thermodynamically stable electrides. Our approach demonstrates a generalizable strategy for targeted materials discovery in a vast chemical space.