First-principles theory, coarse-grained models, and simulations of ferroelectrics

Area of Science:

• Condensed Matter Physics
• Materials Science
• Computational Materials Science

Background:

• Ferroelectric crystals possess spontaneous electric polarization, enabling applications in sensors, actuators, and memory devices.
• Ferroelectric properties are sensitive to chemistry, strain, and interfaces, necessitating accurate theoretical predictions.
• First-principles density functional theory (DFT) provides insights but struggles with large length/time scales for phase transitions.

Purpose of the Study:

• To develop and validate a multiscale modeling strategy for ferroelectric materials.
• To quantitatively predict material-specific ferroelectric phase transitions and properties.
• To gain deeper understanding of ferroelectric transitions, domains, and their underlying mechanisms.

Main Methods:

• Utilized first-principles DFT calculations to derive material-specific model Hamiltonians.
• Employed coarse-graining in the time domain by integrating out high-frequency phonons.
• Performed molecular dynamics simulations on the derived models for bulk and nanoscale ferroelectrics.
• Analyzed free energy landscapes obtained through real-space coarse-graining.

Main Results:

• The multiscale modeling approach successfully predicted material-specific ferroelectric transition behavior.
• Simulations accurately captured temperature-dependent properties in both bulk and nanoscale ferroelectric structures.
• Real-space coarse-graining revealed the critical role of phonon-strain coupling in ferroelectric transitions and domain formation.

Conclusions:

• The developed multiscale modeling strategy offers a powerful tool for studying ferroelectric materials.
• This approach enables quantitative predictions of ferroelectric phenomena across different scales.
• The methodology is applicable to other materials exhibiting complex phase transitions, such as shape memory alloys.