Deep Learning of Accurate Force Field of Ferroelectric HfO${}_2$

Abstract

The discovery of ferroelectricity in HfO${}_2$-based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density non-volatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials is often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network-based interatomic force field of HfO${}_2$ learned from {\em ab initio} data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. The validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO${}_2$ with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO${}_2$ to related material systems including dopants and defects.

References in corpus (6)

• ANI-1: An extensible neural network potential with DFT accuracy at force field computational cost
• The Origin of Ferroelectricity in Hf${}_x$ Zr${}_{1-x}$ O${}_2$: A Computational Investigation and a Surface Energy Model
• Pathways Towards Ferroelectricity in Hafnia
• How van der Waals interactions determine the unique properties of water
• Antiferroelectricity in thin film ZrO2 from first principles
• A computational study of hafnia-based ferroelectric memories: from ab initio via physical modeling to circuit models of ferroelectric device

Cited by in corpus (7)

• Structural Phase Transitions in SrTiO3 from Deep Potential Molecular Dynamics
• Progress in Computational Understanding of Ferroelectric Mechanisms in HfO${}_2$
• Universal interatomic potential for perovskite oxides
• Recent Advances in Unconventional Ferroelectrics and Multiferroics
• A neural-network-backed effective harmonic potential study of the ambient pressure phases of hafnia
• Self-healing mechanism of lithium in lithium metal batteries
• The ground state of CuInP${}_2$S${}_6$ thin films: A study of the deep potential method