Dependence of the structures and chemical ordering of Pd–Pt nanoalloys on potential parameters

The structures and chemical ordering (segregation properties) of Pd–Pt clusters (1 : 1 compositions for N = 2–20 atoms and all compositions for 34 atoms) have been studied using a combination of a genetic algorithm global optimization technique (GA) coupled with the Gupta semi-empirical potential and density functional theory (DFT) calculations. An initial DFT energetic analysis of small Pd–Pt clusters (N = 2–20) showed that their corresponding binding energies are slightly biased towards the stronger metal–metal bonding interactions (i.e. Pt–Pt). This led to a detailed analysis of Pd–Pt structural motifs and segregation effects, where the heteronuclear Pd–Pt parameters in the Gupta potential are derived as weighted averages of the Pd–Pd and Pt–Pt parameters, with the weighting factor (w) ranging from 0 (Pt-biased) to 1 (Pd-biased). The introduction of the weighting factor allowed us to identify three main types of segregation: core–shell; spherical cap; and ball-and-cup (intermediate between the first two types). The structural motifs predicted by the Gupta potential, as a function of composition and potential weighting factor, have been compared to our previous published Gupta and DFT calculations for 34-atom Pt–Pt clusters. From this study, we have found that a slightly Pd-biased weighting factor (w = 0.6) stabilises the mixed decahedral close packed structural motif, previously reported as the DFT global minimum in the region of most exothermic mixing for 34-atom Pd–Pt clusters. Our results show that by finely tuning the Gupta potential, one can qualitatively reproduce structural and chemical ordering patterns observed at higher levels of theory (e.g. DFT).