Ab initio localized basis set study of structural parameters and elastic properties of HfO₂ polymorphs

Area of Science:

• Materials Science
• Computational Physics
• Solid State Chemistry

Background:

• Hafnium dioxide (HfO2) is a crucial material in semiconductor technology.
• Understanding its various phases and properties under pressure is essential for advanced applications.
• Accurate computational methods are needed to predict these properties.

Purpose of the Study:

• To investigate the electronic, elastic, and equilibrium properties of multiple HfO2 phases using the SIESTA approach.
• To evaluate the impact of basis set size, grid density, and pseudization parameters on calculation accuracy.
• To compare computational results with experimental data for phase transitions and structural properties.

Main Methods:

• Utilized the SIESTA (Spanish Initiative for Electronic Simulations with Thousands of Atoms) method.
• Employed separable Troullier-Martins norm-conserving pseudopotentials with partial core corrections for Hf.
• Calculated properties for P21/c, Pbca, Pnma, Fm3m, P42nmc, and Pa3 phases of HfO2.
• Systematically varied basis set size (SZ, DZ), grid density, and pseudization parameters.

Main Results:

• Simple Zeta-LDA (SZ-LDA) calculations improved phase transition pressure predictions compared to Double-Zeta-LDA (DZ-LDA).
• SZ-LDA equilibrium volumes and structural properties showed better agreement with experimental data than GGA.
• DZ-LDA calculations yielded accurate bandgaps, elastic, and structural properties, consistent with advanced ab initio methods and experiments.
• Observed non-linear lattice parameter behavior in the P21/c phase under pressure, matching experimental findings.
• Predicted phase transition pressures of 3.3 GPa and 10.8 GPa for specific transitions using the minimal basis set.

Conclusions:

• The SIESTA approach with minimal basis sets provides accurate predictions for HfO2 properties, particularly phase transition pressures.
• Computational results align well with experimental data, validating the chosen methodology.
• The study highlights the importance of basis set selection and parameter optimization for reliable materials simulations.