2022/01/18 by Ri He, Hongyu Wu, Linfeng Zhang +4 · 71 citations
Chemistry · Materials Science · Physics and Astronomy · #Algorithm #Chemistry #Computer science #Condensed matter physics #Crystallography #Dielectric #Electronic and Structural Properties of Oxides #Ferroelectric and Piezoelectric Materials #Ferroelectricity #Lattice (music) #Machine Learning in Materials Science #Materials science #Nanotechnology #Phase (matter) #Phase diagram #Phase transition #Physics #Quantum mechanics #Strontium titanate #Tetragonal crystal system #Thermodynamics #Thin film #cond-mat.mtrl-sci #physics.app-ph #physics.comp-ph
paper · pdf · doi:10.1103/physrevb.105.064104
published in Physical review. B./Physical review. B 105(6) (American Physical Society)
arxiv created 2022/01/18 · openalex publication_date 2022/02/15 · arxiv updated 2022/03/02 · openalex created_date 2022/04/03 · openalex updated_date 2026/08/05
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.