Quantum Many-Body Simulations of Catalytic Metal Surfaces

TL;DR

This paper introduces FEMION, a new quantum embedding framework that improves the accuracy and scalability of simulations for catalytic metal surfaces, addressing key challenges in computational catalysis.

Contribution

FEMION combines quantum Monte Carlo and RPA methods to accurately model electronic states in metals, enabling predictive simulations of catalytic processes.

Findings

Successfully determined CO adsorption sites on Cu(111)

Quantified H2 desorption barriers on copper surfaces

Extended the 10-electron-count rule to single-atom catalysis

Abstract

Quantum simulations of metal surfaces are critical for catalytic innovation. Yet existing methods face a cost-accuracy dilemma: density functional theory is efficient but system-dependent in accuracy, while wavefunction-based theories are accurate but prohibitively costly. Here we introduce FEMION (Fragment Embedding for Metals and Insulators with Onsite and Nonlocal correlation), a systematically improvable quantum embedding framework that resolves this challenge by capturing partially filled electronic states in metals. FEMION combines auxiliary-field quantum Monte Carlo for local catalytic sites with a global random phase approximation treatment of nonlocal screening, yielding a scalable approach across diverse catalytic systems. Employing FEMION, we address two longstanding challenges: determining the preferred CO adsorption site and quantifying the H2 desorption barrier on Cu(111). Furthermore, our calculations demonstrate that the recently discovered 10-electron-count rule can also be extended to the single-atom catalysis processes on 3d metal surfaces, resolving the controversies arising from density functional theory calculations. We thus open a predictive, first-principles route to modeling complex catalytic systems.