Oxidation and de-alloying of PtMn particle models: a computational investigation

Abstract

We present a computational study of the energetics and mechanisms of oxidation of Pt–Mn systems. We use slab models and simulate the oxidation process over the most stable (111) facet at a given Pt₂Mn composition to make the problem computationally affordable, and combine Density-Functional Theory (DFT) with neural network potentials and metadynamics simulations to accelerate the mechanistic search. We find, first, that Mn has a strong tendency to alloy with Pt. This tendency is optimally realized when Pt and Mn are mixed in the bulk, but, at a composition in which the Mn content is high enough such as for Pt₂Mn, Mn atoms will also be found in the surface outmost layer. These surface Mn atoms can dissociate O₂ and generate MnO_x species, transforming the surface-alloyed Mn atoms into MnO_x surface oxide structures supported on a metallic framework in which one or more vacancy sites are simultaneously created. The thus-formed vacancies promote the successive steps of the oxidation process: the vacancy sites can be filled by surface oxygen atoms, which can then interact with Mn atoms in deeper layers, or subsurface Mn atoms can intercalate into interstitial sites. Both these steps facilitate the extraction of further bulk Mn atoms into MnO_x oxide surface structures, and thus the progress of the oxidation process, with typical rate-determining energy barriers in the range 0.9–1.0 eV.