Structure‐Sensitive Scaling Relations: Adsorption Energies from Surface Site Stability

Abstract

The design of heterogeneous catalysts is accelerated by the identification of thermochemical reactivity descriptors, which enable the prediction of promising materials through efficient screening. Motivated by previous discoveries of linear scaling relations between the adsorption energies of related atoms and molecules, we present a new scaling between the adsorption energies of metal atoms and metal–adsorbate complexes, which can be used to directly predict catalytically relevant molecular adsorption energies. In contrast to existing models based on the coordination number of surface atoms alone, our model can predict adsorption energies with site‐by‐site resolution considering local structural effects and also has potential extensions to include contributions of neighboring metal identity in alloy systems. Integration of this scaling with a previously identified model for metal–metal interactions enables the accurate prediction of molecular adsorption energies on nanoparticles by performing only a small set of slab‐based calculations.

Size‐Dependence of the Melting Temperature of Individual Au Nanoparticles

“…The particle shape has a significant influence on the melting temperature, as it affects the surface energy. Roling and Abild‐Pedersen have shown how the binding energy of surface atoms of the nanoparticle depends on their coordination number . The ratio of atoms in lower‐coordinated sites (edges and vertexes) increases with inverse particle diameter and this results in a gradual decrease in surface energy .…”

Unfolding adsorption on metal nanoparticles: Connecting stability with catalysis

“…This model corresponds to case (ii) of Table 1. ( C ) The model trained on PBE DFT data for NPs (Au/Ag/Cu, 55 to 172 atoms) and tested against RPBE DFT data for top-site adsorptions on metal surfaces (Au/Ag/Cu) from the literature slab dataset ( 29 ). This model corresponds to case (ii) of Table 1.…”

“…In addition to nonperiodic NP systems, we also investigated periodic (slab) systems. Recently, Roling and Abild-Pedersen ( 29 ) developed several scaling relations for adsorption on metal slabs and, alongside these relations, reported a large body of DFT calculations describing the adsorption of CH 3, CO, and OH on the surface of several metal slabs of Ag, Au, Cu, Ir, Ni, Pd, Pt, and Rh. Using the scaling relations, they derive a model that describes metal-adsorbate BEs to a high degree of accuracy but is parameterized by several DFT calculations.…”

Machine Learning for Computational Heterogeneous Catalysis

“…Generalized and orbital‐wise coordination numbers have been successfully used as features in linear scaling relations between DFT adsorption energies on mono‐metallic surfaces . An alternative purely coordination‐based approach uses the binding energy of the metal adsorption sites as a feature to predict adsorption energies of thermo‐chemical descriptors on mono‐metallic surfaces and nanoparticles . This approach unveils a new family of linear scaling relations between adsorption site stabilities and adsorption energies.…”

“…The analysis of linear regression coefficients has brought insights about the role of the bond order between adsorbate and surface in scaling relations using the to C scaling as an example (Figure ). This observation has enabled a fundamental understanding of the parameters that define catalytic activity . Linear regression has furthermore been successfully used to predict the d ‐band center within a mean absolute error of about 0.26 eV from a set of experimental elementary descriptors .…”