(684d) Towards Swift Predictions of Metal Ad-Atom Diffusion Barriers and Surface Energies for Enhanced Understanding of Sintering and Catalysts Durability

In the realm of heterogeneous catalysis, whether thermal or electrochemical, the durability and morphology/shapes of active metal sites under reaction conditions are areas of great importance. Our research aims to better understand the dynamics of catalytic systems by building upon previously developed coordination-based approaches [1] that effectively predicted general configurational energies of metal nanostructures. However, up until now, this generalized scheme has not been directly parameterized to understand the stability of adatoms during non-equilibrium states of diffusion/migration, since partial coordination to neighboring atoms is not explicitly defined under the scheme. Therefore, we evaluate stability of metal atoms by using density functional theory (DFT) to calculate activation energies for atomic diffusions/migrations over various FCC surfaces. From these, we then extract coordination-based parameters to fit to the energies of atoms at non-equilibrium distances. We use this extended model to gain enhanced understanding of surface restructuring and sintering in heterogeneous catalytic contexts e.g. Cu catalysts during electrochemical CO₂ reduction.

Since the activation of reactants in heterogenous catalysis occur through interactions with surface active sites, surface properties, specifically surface energies and the distribution of site morphologies are vital for optimization of catalytic activity and selectivity. Therefore, using mentioned coordination schemes, we also evaluate surface energies and predict relative stabilities of various catalytic surfaces with periodic slabs as well as various metal nanoparticle (MNP) shapes. Finally, extension of surface energy and activation barrier calculations to multimetallic surfaces (alloys) are discussed. This leads to effective screening of thermodynamic stabilities of alloy MNPs, by integrating coordination schemes with structural and site information. The resulting models can then be applied to calculate the energetics of any nanoparticle morphology and chemical composition, thus significantly accelerating design of durable nanoalloys.

References

1. Roling, L.T., L. Li, and F. Abild-Pedersen, The Journal of Physical Chemistry C, 2017. 121(41): p. 23002-23010.