Determining ground states of alloy by a symmetry-based classification

TL;DR

This paper introduces a symmetry-based atom classification model to efficiently identify ground state structures of alloys, reducing computational effort and predicting new stable configurations.

Contribution

The study presents a novel symmetry-based classification approach that streamlines candidate structure generation for alloy ground state determination, incorporating geometric symmetry effects.

Findings

Successfully identified known stable alloy structures.

Predicted new low-energy alloy configurations.

Demonstrated the correlation between symmetry and structural stability.

Abstract

Reducing the number of candidate structures is crucial to improve the efficiency of global optimization. Herein, we demonstrate that the generalized Hamiltonian can be described by the atom classification model (ACM) based on symmetry, generating competent candidates for the first-principles calculations to determine ground states of alloy directly. The candidates can be obtained in advance through solving the convex hull step by step, because the correlation functions of ACM can be divided into various subspace according to the defined index $l$. As an important inference, this index can be converted to the number of Wyckoff positions, revealing the dominant effect of geometry symmetry on structural stability. Taking Ni-Pt, Ag-Pd, Os-Ru, Ir-Ru and Mo-Ru as examples, we not only identify the stable structures in previous theoretical and experimental results, but also predict a dozen of configurations with lower formation energies, such as Ag$_{0.5}$Pd$_{0.5}$ ($Fd$-$3m$), Os$_{0.5}$Ru$_{0.5}$ ($Pnma$), Ir$_{1/3}$Ru$_{2/3}$ ($P6_{3}/mmc$), and Mo$_{0.25}$Ru$_{0.75}$ ($Cmcm$).