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

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
using the same physics in a many-body perturbative approach that can
be more accurate than generalized-gradient density functional theory
(DFT) methods. However, GW/RPA implementations have historically been
limited to either specific materials classes or application toward
small chemical systems. The static subspace approximation allows for
reduced cost full-frequency GW/RPA calculations and has previously
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.
We benchmarked RPA total energy calculations using the subspace approximation
across a diverse test suite of materials for a variety of computational
parameters. The benchmarking quantifies the impact of different extrapolation
procedures for representing the static polarizability at infinite
screened cutoff, and shows that using screened cutoffs above 20–25
Ryd result in diminishing accuracy returns for predicting RPA total
energies. Additionally, for moderately sized electrocatalytic models,
2–3 times fewer computational resources are used to compute
RPA total energies by representing the static polarizability with
20–30% of the static subspace basis, with an error of approximately
0.01 eV or better in RPA adsorption energy calculations. Finally,
we show that for these electrochemical models RPA can shift DFT adsorption
energy shifts by up to 0.5 eV and that GW can frequently shift DFT
eigenvalues of surface and adsorbate states by approximately 0.5–1
eV.