Structural Phase Transitions in SrTiO3 from Deep Potential Molecular Dynamics

TL;DR

This paper develops a machine learning-based deep potential model for SrTiO3, enabling accurate and efficient molecular dynamics simulations of its temperature-driven cubic-to-tetragonal phase transition and strain effects.

Contribution

The authors create a DFT-level accurate deep potential model for SrTiO3, facilitating detailed atomistic simulations of phase transitions and strain effects not previously possible with empirical potentials.

Findings

Strain-induced ferroelectric phase characterized by two order parameters.

The phase transition exhibits both displacive and order-disorder characters.

Constructed a strain-temperature phase diagram for SrTiO3.

Abstract

Strontium titanate (SrTiO3) is regarded as an essential material for oxide electronics. One of its many remarkable features is subtle structural phase transition, driven by antiferrodistortive lattice mode, from a high-temperature cubic phase to a low-temperature tetragonal phase. Classical molecular dynamics (MD) simulation is an efficient technique to reveal atomistic features of phase transition, but its application is often limited by the accuracy of empirical interatomic potentials. Here, we develop an accurate deep potential (DP) model of SrTiO3 based on a machine learning method using data from first-principles density functional theory (DFT) calculations. The DP model has DFT-level accuracy, capable of performing efficient MD simulations and accurate property predictions. Using the DP model, we investigate the temperature-driven cubic-to-tetragonal phase transition and construct the in-plane biaxial strain-temperature phase diagram of SrTiO3. The simulations demonstrate that strain-induced ferroelectric phase is characterized by two order parameters, ferroelectric distortion and antiferrodistortion, and the ferroelectric phase transition has both displacive and order-disorder characters. This works lays the foundation for the development of accurate DP models of other complex perovskite materials.