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

## TL;DR

The paper introduces a high-accuracy quantum method for simulating surface chemistry, enabling large-scale simulations with GPU acceleration and matching experimental results.

## Contribution

A multi-resolution, systematically improvable quantum embedding scheme with linear scaling for large surface chemistry simulations.

## Key findings

- Achieved gold standard accuracy for surface chemistry simulations up to 392 atoms using GPU acceleration.
- Demonstrated consistent results for water-graphene interactions across different boundary conditions.
- Provided chemically accurate simulations of carbonaceous molecule adsorption on complex surfaces.

## 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.

Surfaces are the stage for vital catalytic reactions, but accurately simulating them is computationally expensive. Here, the authors introduce an efficient method using GPUs to model large, complex surfaces with exceptionally high, experiment-matching accuracy