Fast Prediction of Adsorption Properties for Platinum Nanocatalysts with Generalized Coordination Numbers

Platinum is a prominent catalyst for a multiplicity of reactions because of its high activity and stability. As Pt nanoparticles are normally used to maximize catalyst utilization and to minimize catalyst loading, it is important to rationalize and predict catalytic activity trends in nanoparticles in simple terms, while being able to compare these trends with those of extended surfaces. The trends in the adsorption energies of small oxygen- and hydrogen-containing adsorbates on Pt nanoparticles of various sizes and on extended surfaces were analyzed through DFT calculations by making use of the generalized coordination numbers of the surface sites. This simple and predictive descriptor links the geometric arrangement of a surface to its adsorption properties. It generates linear adsorption-energy trends, captures finite-size effects, and provides more accurate descriptions than d-band centers and usual coordination numbers. Unlike electronic-structure descriptors, which require knowledge of the densities of states, it is calculated manually. Finally, it was shown that an approximate equivalence exists between generalized coordination numbers and d-band centers.