Effect of uniaxial compressive stress on polarization switching and domain wall formation in tetragonal phase BaTiO3 via machine learning potential
Po-Yen Chen, Teruyasu Mizoguchi

TL;DR
This study uses machine learning potentials to explore how uniaxial compressive stress influences polarization switching and domain wall formation in tetragonal BaTiO3, revealing critical stress thresholds and effects on ferroelectric properties.
Contribution
It introduces a machine learning interatomic potential to analyze stress effects on polarization and domain walls in BaTiO3, providing atomistic insights into mechanical control of ferroelectric switching.
Findings
A critical stress of about 120 MPa induces 90-degree polarization switching.
Larger supercells show lower activation energies for polarization switching beyond the critical stress.
Increasing compressive stress reduces remnant polarization and coercive field, with a double hysteresis loop at 80 MPa.
Abstract
Ferroelectric materials such as BaTiO3 exhibit spontaneous polarization that can be reoriented by an external electric field, forming the basis of various memory, actuator, and sensor applications. The polarization switching behavior, however, is strongly influenced by mechanical boundary conditions due to the intrinsic electromechanical coupling in ferroelectrics. In this study, we employ a machine learning interatomic potential to investigate the effect of uniaxial compressive stress on polarization switching and domain wall evolution in the tetragonal phase of BaTiO3. This study revealed a critical stress about 120 MPa which 90 degree polarization switching occurs. Beyond the critical stress, larger supercells exhibit lower activation energies for polarization switching with 180-degree domain wall formation and weaker constraints from periodic boundary conditions, thereby…
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