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

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Authors: Neung-Kyung Yu, Johannes Voss, Andrew James Medford
Cited by: 0

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.

Fields of Study & Subjects

Advanced Chemical Physics Studies Machine Learning in Materials Science Advanced Physical and Chemical Molecular Interactions

Publication details

Journal / source
arXiv (Cornell University)
Publication date
4 February 2026
Document type
Preprint