A multi-resolution systematically improvable quantum embedding scheme for large-scale surface chemistry calculations.

Abstract

Predictive simulation of surface chemistry is critical in fields from catalysis to electrochemistry and clean energy generation. Ab-initio quantum many-body methods should offer deep insights into these systems at the electronic level but are limited by their steep computational cost. Here, we build upon state-of-the-art correlated wavefunctions to reliably reach 'gold standard' accuracy in quantum chemistry for extended surface chemistry. Efficiently harnessing graphics processing unit acceleration along with systematically improvable multi-resolution techniques, we achieve linear computational scaling up to 392 atoms. These large-scale simulations demonstrate the importance of converging to these extended system sizes, achieving consistency between simulations with different boundary conditions for the interaction of water on a graphene surface. We provide a benchmark for this water-graphene interaction that clarifies the preference for water orientations at the graphene interface. This is extended to the adsorption of carbonaceous molecules on chemically complex surfaces, including metal oxides and metal-organic frameworks, where we consistently achieve chemical accuracy compared to experimental references. This advances the simulation of molecular adsorption on surfaces, enabling reliable and improvable first-principles modeling of such problems by ab-initio quantum many-body methods.