Optimization of random phase approximation calculations for improved energies of molecules, solids, and surfaces

TL;DR

This paper introduces optRPA26, an optimized RPA method that uses a hybrid functional for DFT orbitals and scaling to significantly enhance the accuracy of energy calculations across molecules, solids, and surfaces.

Contribution

The paper presents a new optimized RPA approach, optRPA26, which improves energy accuracy and can be implemented with standard RPA codes for diverse bonding types.

Findings

Achieves mean absolute errors of 0.05-0.12 eV across benchmarks.

Accurately captures phase stability in oxides and metals.

Compatible with standard RPA implementations.

Abstract

We present an optimized random phase approximation method (optRPA26) that significantly improves upon conventional RPA. The method employs an empirically constructed hybrid functional to generate DFT orbitals to evaluate the RPA correlation energy, which is then scaled by a constant. Comprehensive benchmarks across molecules, bulk solids, and surface systems demonstrate that optRPA26 consistently achieves high accuracy, with mean absolute errors of 0.05 eV for W4-11 reaction energies, 0.07 eV for cohesive energies, 0.09 eV for metal oxide formation energies, 0.11-0.12 eV for adsorption of small molecules on metals, and 0.06 eV for adsorption on oxides. In addition, optRPA26 correctly captures phase stability in metal oxides and magnetic metals. The optRPA26 approach can be run using standard RPA implementations, highlighting its potential as a general-purpose reference method that can accurately capture covalent, ionic, and metallic, and van der Waals bonding in molecules, solids, and interfaces.