Special quasirandom structures for perovskite solid solutions.

Area of Science:

• Materials Science
• Solid-State Physics
• Computational Chemistry

Background:

• Disordered perovskite solid solutions present significant challenges in materials modeling.
• Accurate representation of atomic arrangements is crucial for predicting material properties.

Purpose of the Study:

• To generate and validate Special Quasirandom Structures (SQS) for various perovskite compositions.
• To assess the efficacy of SQS in predicting diverse physical properties of disordered perovskites.
• To compare SQS predictions with results from large random supercells.

Main Methods:

• Generation of SQS configurations for perovskite alloys (A'1-xBx3 and A(B'1-xX)X3) with varying compositions (x=1/2, 1/3, 2/3).
• Minimization of Cowley parameters for the nearest neighboring shells in SQS.
• Application of effective Hamiltonian schemes to predict properties using SQS.
• Comparison of SQS-derived properties with those from large random supercells for compounds like (Ba1-xSrx)TiO3 and Pb(Zr1-xTix)O3.

Main Results:

• SQS configurations successfully reproduce numerous properties of large random supercells for most disordered perovskite alloys.
• Predicted properties include electrical polarization, octahedral tiltings, antipolar motions, antiferromagnetism, strain, piezoelectricity, dielectric response, and specific heat.
• Formation of polar nanoregions (PNRs) in relaxors was also reproduced.
• Limitations of SQS configurations were identified and explained.

Conclusions:

• SQS are a powerful tool for simulating disordered perovskite materials, offering a good balance between accuracy and computational cost.
• SQS can reliably predict a wide range of physical properties below a material-dependent temperature.
• The study provides insights into the applicability and limitations of SQS in materials design and discovery.