PdnAg(4−n) and PdnPt(4−n) clusters on MgO (100): a density functional surface genetic algorithm investigation
The novel surface mode of the Birmingham Cluster Genetic Algorithm (S-BCGA) is employed for the global optimisation of noble metal tetramers upon an MgO (100) substrate at the GGA-DFT level of theory. The effect of element identity and alloying in surface-bound neutral subnanometre clusters is determined by energetic comparison between all compositions of PdnAg(4−n) and PdnPt(4−n). While the binding strengths to the surface increase in the order Pt > Pd > Ag, the excess energy profiles suggest a preference for mixed clusters for both cases. The binding of CO is also modelled, showing that the adsorption site can be predicted solely by electrophilicity. Comparison to CO binding on a single metal atom shows a reversal of the 5σ–d activation process for clusters, weakening the cluster–surface interaction on CO adsorption. Charge localisation determines homotop, CO binding and surface site preferences. The electronic behaviour, which is intermediate between molecular and metallic particles allows for tunable features in the subnanometre size range.