Quantitative evaluation of nuclear quantum effects on the phase transitions in BaTiO₃using large-scale molecular...

Area of Science:

• Materials Science
• Computational Physics
• Quantum Mechanics

Background:

• Barium titanate (BaTiO3) is a key ferroelectric material with complex phase transitions.
• Understanding these transitions is crucial for its applications in electronics.
• Previous studies often neglected or approximated nuclear quantum effects (NQEs).

Purpose of the Study:

• To construct the pressure-temperature phase diagram of BaTiO3 using machine learning potential-based molecular dynamics (MLPMD).
• To quantitatively evaluate the impact of NQEs on BaTiO3 phase transitions.
• To investigate the microscopic mechanism of the tetragonal-cubic phase transition.

Main Methods:

• Employed machine learning potential-based molecular dynamics (MLPMD) for phase diagram construction.
• Incorporated nuclear quantum effects (NQEs) using the quantum thermal bath (QTB) method.
• Utilized a large simulation cell (20x20x20 supercell) without degree of freedom restrictions.

Main Results:

• Constructed a pressure-temperature phase diagram for BaTiO3, showing NQEs lower transition temperatures and pressures.
• Demonstrated that NQEs are significant at lower temperatures and still relevant at room temperature.
• Observed that the tetragonal-cubic phase transition is displacive, differing from previous order-disorder findings.

Conclusions:

• NQEs play a critical role in BaTiO3 phase transitions, affecting both thermodynamic and microscopic properties.
• The QTB-MLPMD method provides accurate phase diagrams consistent with experimental and other simulation results.
• Discrepancies in observed transition mechanisms may stem from simulation cell size and lattice dynamics restrictions in prior studies.