Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry

31 May 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Modeling complex materials using high-fidelity, ab-initio methods at low cost is a fundamental goal for quantum chemical software packages. The GW approximation and random phase approximation (RPA) provide a unified description of both electronic structure and total energies more accurate than density functional theory (DFT) methods by using the same physics in a many-body perturbative approach. However, GW/RPA implementations have historically been limited to either specific materials classes or application towards small chemical systems. The static subspace approximation allows for reduced cost full-frequency GW/RPA calculations and has been benchmarked thoroughly for GW calculations. Here, we describe our approach to including partial occupations of electronic orbitals in full-frequency GW and RPA calculations for the study of electrocatalysts, and we benchmark RPA total energies with the subspace approximation across a diverse testsuite of materials, providing recommendations of best practices for such calculations. Finally, we provide examples of physically relevant catalyst surfaces models studied using GW/RPA.

Supplementary materials

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Supporting data of RPA benchmarks
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Additional convergence data
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