Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for...

Area of Science:

• Computational Chemistry
• Materials Science
• Quantum Mechanics

Background:

• Accurate modeling of complex materials using ab initio methods is crucial for quantum chemical software.
• GW approximation and RPA offer accurate electronic structure and energy calculations, surpassing traditional DFT.
• Previous GW/RPA implementations were limited by system size and material class.

Purpose of the Study:

• To develop and validate a cost-effective method for full-frequency GW and RPA calculations.
• To enable the study of electrocatalysts with high-fidelity quantum chemical methods.
• To investigate the impact of partial orbital occupations in GW/RPA for materials modeling.

Main Methods:

• Implementation of partial orbital occupations in full-frequency GW and RPA.
• Utilizing the static subspace approximation for reduced computational cost.
• Benchmarking RPA total energy calculations across diverse materials and computational parameters.

Main Results:

• The static subspace approximation significantly reduces computational resources (2-3x) for RPA total energies.
• Screened cutoffs above 20-25 Ryd show diminishing returns in accuracy for RPA total energies.
• RPA adsorption energies were computed with errors of ~0.01 eV or better using a fraction of the static subspace basis.
• RPA and GW methods can shift DFT adsorption energies and eigenvalues by up to 0.5-1 eV.

Conclusions:

• The developed method enhances the applicability of GW/RPA to complex materials, particularly electrocatalysts.
• The static subspace approximation offers a practical balance between accuracy and computational cost.
• These findings pave the way for more accurate and efficient materials design and discovery.