Screening 39 billion protostructures for materials discovery

TL;DR

This paper presents a large-scale computational screening of 39 billion inorganic protostructures to identify promising stable crystal candidates for materials discovery, significantly expanding known structural databases.

Contribution

The study introduces a high-throughput energy screening method that explores an unprecedented number of protostructures, generating a vast dataset of 81 million relaxed crystals and 88,498 new prototypes.

Findings

Identification of 88,498 new crystal prototypes.

Validation of methods on known materials systems.

Creation of a comprehensive map of low-energy structures.

Abstract

Large-scale computational surveys are increasingly used to map the landscape of stable crystalline materials. We report a high-throughput energy screening of inorganic crystals that enumerates binary and ternary compositions up to a specified unit-cell complexity, yielding 39 billion protostructures. Candidates predicted to lie on or near the convex hull are retained, and their degrees of freedom are explored via Latin hypercube sampling followed by relaxation with machine-learned interatomic potentials. The resulting dataset contains 81 million locally relaxed crystal structures spanning 4495 ternary phase diagrams constructed from elements ranging from lithium to bromine and contains 88,498 crystal prototypes not present in existing crystal-structure databases. The methods are validated both for three well-explored materials systems, Zr-Zn-N, Ti-Zn-N, and Hf-Zn-N, and by comparing with known data for structures resulting from the larger screening. The work provides a systematic map of low-energy compositional-structural space and a large, structured pool of candidates for downstream property evaluation and materials design.