Introducing the embedded random phase approximation: H2 dissociative adsorption on Cu(111) as an exemplar

Area of Science:

• Computational Chemistry
• Materials Science
• Surface Science

Background:

• The random phase approximation (RPA) shows promise for electron correlation, outperforming standard density functional theory (DFT) in certain cases.
• However, the high computational cost of RPA, especially for extended surfaces, limits its application.
• Accurate modeling requires addressing surface ensemble size, Brillouin zone sampling, and vacuum separation in periodic calculations.

Purpose of the Study:

• To investigate sub-system embedding schemes for reducing the computational cost of RPA calculations for heterogeneous reactions.
• To compare the accuracy and efficiency of periodic embedded RPA (emb-RPA) and cluster embedded RPA (cluster emb-RPA).
• To demonstrate the feasibility of using embedded RPA for modeling catalytic processes.

Main Methods:

• Full periodic RPA calculations were performed as a benchmark for H2 dissociative adsorption on Cu(111).
• Two embedded RPA approaches, periodic emb-RPA and cluster emb-RPA, were explored.
• The results were compared against experimental data and high-level computational methods like embedded n-electron valence second-order perturbation theory and quantum Monte Carlo.

Main Results:

• Full RPA calculations provided results consistent with experimental data and other high-level computational benchmarks.
• The cluster emb-RPA approach accurately reproduced the reaction energy profile with a maximum error of 50 meV.
• Cluster emb-RPA achieved a significant reduction in computational cost, approximately two orders of magnitude, compared to full periodic RPA.

Conclusions:

• Sub-system embedding schemes, particularly cluster emb-RPA, enable the use of RPA for modeling heterogeneous reactions at a reduced computational cost.
• The cluster embedded approach offers a computationally efficient and accurate method for studying surface phenomena.
• This work paves the way for broader implementation of RPA in heterogeneous catalysis research.