Stability of Bimetallic Pt _x Ru _y - From Model Surfaces to Nanoparticulate Electrocatalysts

Fundamental research campaigns in electrocatalysis often involve the use of model systems, such as single crystals or magnetron-sputtered thin films (single metals or metal alloys). The downsides of these approaches are that oftentimes only a limited number of compositions are picked and tested (guided by chemical intuition) and that the validity of trends is not verified under operating conditions typically present in real devices. These together can lead to deficient conclusions, hampering the direct application of newly discovered systems in real devices. In this contribution, the stability of magnetron-sputtered bimetallic PtxRuy thin film electrocatalysts (0 at. % to 100 at. % Ru content) along with three commercially available carbon-supported counterparts (50-67 at. % Ru content) was mapped under electrocatalytic conditions in acidic electrolytes using online ICP-MS. We found several differences between the two systems in the amount of metals dissolved along with the development of the morphology and composition. While the Pt-rich PtxRuy compositions remained unchanged, 30-50 nm diameter surface pits were detected in the case of the Ru-rich sputtered thin films. Contrastingly, the surface of the carbon-supported NPs enriched in Pt accompanied by the leaching of a significant amount of Ru from the alloy structure was observed. Change in morphology was accompanied by a mass loss reaching around 1-2 wt % in the case of the sputtered samples and almost 10 wt % for the NPs. Since PtxRuy has prime importance in driving alcohol oxidation reactions, the stability of all investigated alloys was screened in the presence of isopropanol. While Pt dissolution was marginally affected by the presence of isopropanol, several times higher Ru dissolution was detected, especially in the case of the Ru-rich compositions. Our results underline that trends in terms of electrocatalytic activity and stability cannot always be transferred from model samples to systems that are closer to the ones applied in real devices.