An Element-Based Generalized Coordination Number for Predicting the Oxygen Binding Energy on Pt3M (M = Co, Ni, or Cu) Alloy Nanoparticles.

We studied the binding energies of O species on face-centered-cubic Pt3M nanoparticles (NPs) with a Pt-skin layer using density functional theory calculations, where M is Co, Ni, or Cu. It is desirable to express the property by structural parameters rather than by calculated electronic structures such as the d-band center. A generalized coordination number (GCN) is an effective descriptor to predict atomic or molecular adsorption energy on Pt-NPs. The GCN was extended to the prediction of highly active sites for oxygen reduction reaction. However, it failed to explain the O binding energies on Pt-skin Pt150M51-NPs. In this study, we introduced an element-based GCN, denoted as GCNA-B, and considered it as a descriptor for supervised learning. The obtained regression coefficients of GCNPt-Pt were smaller than those of the other GCNA-B. With increasing M atoms in the subsurface layer, GCNPt-M, GCNM-Pt, and GCNM-M increased. These factors could reproduce the calculated result that the O binding energies of the Pt-skin Pt150M51-NPs were less negative than those of the Pt201-NPs. Thus, GCNA-B explains the ligand effect of the O binding energy on the Pt-skin Pt150M51-NPs.