Parts | Days | Selection | Search | Updates | Downloads | Help

O: Fachverband Oberflächenphysik

O 52: Heterogeneous Catalysis and Surface Dynamics I

O 52.4: Topical Talk

Wednesday, March 29, 2023, 11:15–11:45, TRE Phy

Modeling and Design of Single-Atom Alloy Catalysts — Raffaele Cheula and •Mie Andersen — Department of Physics and Astronomy, Aarhus University, Denmark

In this contribution we apply molecular simulations and machine learning (ML) to study CO₂ hydrogenation (reverse water-gas shift) on single-atom alloy (SAA) catalysts, i.e., diluted bimetallic materials. SAAs have been shown to be able to break the scaling relationships that limit conventional catalysts [1]. We target a wide combinatorial space of elements of the periodic table, which makes a direct study with density-functional theory (DFT) computationally prohibitive. Therefore, we produce a database of DFT-calculated energies on a limited number of SAAs and apply physics-inspired ML techniques for the extrapolation to a wide range of materials. We use a graph-based Gaussian Process Regression ML model (WWL-GPR [2]) to calculate adsorption energies, and simpler models (e.g., multivariate regressions) to estimate the activation energies of the new materials. We employ microkinetic modeling to simulate the reaction kinetics; then, we apply sensitivity analysis and uncertainty quantification to identify the parameters that can improve the model predictions, and we refine them with additional DFT calculations. The application of the framework to CO₂ hydrogenation allows us to rationalize how reaction mechanisms and catalytic activity change with the catalyst composition, paving the way toward the design and nano-engineering of SAA catalysts.

[1] RT. Hannagan et al., Chem. Rev. 120, 12044 (2020)

[2] W. Xu et al., Nat. Comp. Sci. 2, 443 (2022)