![]() 1Key Laboratory of Magnetic Materials Devices & Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China.Ri He 1,*, Hongyu Wu 1,*, Linfeng Zhang 2,3, Xiaoxu Wang 2,3, Fangjia Fu 3,4, Shi Liu 5,6,7,†, and Zhicheng Zhong 1,8,‡ In this paper, we lay the foundation for the development of accurate DP models of other complex perovskite materials. The simulations demonstrate that the strain-induced ferroelectric (FE) phase is characterized by two order parameters, FE distortion and antiferrodistortion, and the FE phase transition has both displacive and order-disorder characters. 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 SrTi O 3. The DP model has DFT-level accuracy, capable of performing efficient MD simulations and accurate property predictions. Here, we develop an accurate deep potential (DP) model of SrTi O 3 based on a machine learning method using data from first-principles density functional theory (DFT) calculations. 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. One of its many remarkable features is the subtle structural phase transition, driven by the antiferrodistortive lattice mode, from a high-temperature cubic phase to a low-temperature tetragonal phase. Strontium titanate ( SrTi O 3) is regarded as an essential material for oxide electronics. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |