Predicting Interface Structure using the Minima Hopping Method with a Machine Learning Interatomic Potential

TL;DR

This paper introduces a combined computational approach using Minima Hopping and machine learning interatomic potentials to efficiently predict complex interfacial structures in materials, validated against experimental data.

Contribution

The study presents a novel integration of Minima Hopping with MLIP Allegro for accurate, efficient interface structure prediction without needing defective configurations in training datasets.

Findings

Successfully predicts lowest-energy interface structures in SrTiO3

Achieves strong agreement with experimental interfacial configurations

Demonstrates efficient and robust prediction methodology

Abstract

Predicting atomic-scale interfacial structures remains a central challenge in materials science due to their structural complexity and the difficulty of direct comparison between computational and experimental results. In this study, we present an efficient approach for interface structure prediction that integrates the Minima Hopping Method (MHM) with the state-of-the-art machine learning interatomic potential (MLIP), Allegro. We demonstrate that the MHM-Allegro approach provides a robust and computationally efficient route for predicting interfacial structures in the benchmark system SrTiO3 Sigma 3 (112)[110] tilt grain boundaries (GBs), consistently identifying the lowest-energy configurations across different stoichiometries. Furthermore, we introduce a strategy for constructing defect-representative training datasets without explicitly including defective configurations, achieving excellent extrapolative performance in interface predictions. The predictive capability is further validated through direct comparison with experimental observations of the SrTiO3 Sigma 5 (310)[001] GB, where the predicted atomic configurations show strong agreement with experimental measurements. This work represents a significant step toward bridging the gap between ab initio predictions and experimentally observed interfacial structures.