Global optimization of Pd-Au bimetallic clusters in the size range N ) 2-50 has been performed using a genetic algorithm, coupled with the Gupta many-body empirical potential (EP) to model interatomic interactions. Three sets of EP parameters have been examined in this work: (a) an average of pure Pd and Au parameters, (b) experimental Pd-Au-fitted parameters, and (c) DFT-fitted parameters. Stability criteria, such as binding energy and second difference in energy, have been used to determine the lowest energy structures, that is, the global minima (GM). DFT local relaxations have been performed on all the "putative" GM structures for 1:1 compositions of (Pd-Au) N/2 up to N ) 50 for the three sets of EP parameters. It is found that the average parameter set a leads to a Pd core Au shell segregation, whereas the fitted parameter sets b and c lead to more Pd-Au mixing. DFT reoptimization of the structures produced by potentials a, b, and c shows small differences in binding energies. In addition, 34-and 38-atom Pd-Au clusters were studied using these three Gupta potential parametrizations as a function of composition and analyzed in terms of their mixing energies and chemical order parameters. DFT relaxations were performed on the lowest mixing energy compositions, allowing us to have a clearer description of the energy landscape for all three EP parameter sets at these cluster sizes. For the compositions, Pd 17 Au 17 and Pd 19 Au 19 , DFT calculations confirm that some degree of Au surface segregation is energetically preferred, though it is not necessarily complete Pd core Au shell segregation, as predicted by the average potential a.

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Global optimizations via a genetic algorithm using the Gupta empirical potential are performed on 34-atom Pd-Pt binary clusters, finding a complex crossover among several structural motifs that are close in energy. The composition range is then restricted on the basis of stability criteria; (a) the Gupta global minima at each composition are subjected to density functional (DFT) local energy minimizations, and (b) at the 24-10 composition, the lowest-energy isomers of each structural family are locally optimized at the DFT level. It is found that the energetic ordering of the structural motifs predicted by the Gupta potential is not confirmed at the DFT level and that a new structural motif, a mixed decahedral/close-packed (Dh-cp(DT)) one, is the putative global minimum at all compositions. Finally, segregation effects of Pd atoms to the surface of the cluster are studied at the composition Pd 17 Pt 17 and found to be corroborated by DFT calculations. The peculiar stability of the Dh-cp(DT) arrangement is rationalized in terms of an optimal compromise between coresegregated, and thus preferentially close-packed, Pt atoms and surface-segregated, and thus preferentially decahedral, Pd atoms.

The energetics of 98 atom bimetallic Pd-Pt clusters are studied using a combination of: a genetic algorithm technique (to explore vast areas of the configurational space); a basin-hopping atom-exchange routine (to search for lowest-energy homotops at fixed composition); and a shell optimisation approach (to search for high symmetry isomers). The interatomic interactions between Pd and Pt are modelled by the Gupta many-body empirical potential. For most compositions, the putative global minima are found to have structures based on defective Marks decahedra, but in the composition range from Pd46Pt52 to Pd63Pt35, the Leary tetrahedron (LT)--a structure previously identified for 98 atom Lennard-Jones clusters--is consistently found as the most stable structure. Based on the excess energy stability criterion, Pd56Pt42 represents the most stable cluster across the entire composition range. This structure, a Td-symmetry LT, exhibits multi-layer segregation with an innermost core of Pd atoms, an intermediate layer of Pt atoms and an outermost Pd surface shell (Pd-Pt-Pd). The stability of the Leary tetrahedron is compared against other low-energy competing structural motifs: the Marks decahedron (Dh-M), a "quasi" tetrahedron (a closed-packed structure) and two other closed-packed structures. The stability of LT structures is rationalized in terms of their spherical shape and the large number of nearest neighbours.

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The energetics, structures and segregation of 98-atom AuPd nanoclusters are investigated using a genetic algorithm global optimization technique with the Gupta empirical potential (comparing three different potential parameterisations) followed by local minimizations using Density Functional Theory (DFT) calculations. A shell optimization program algorithm is employed in order to study the energetics of the highly symmetric Leary Tetrahedron (LT) structure and optimization of the chemical ordering of a number of structural motifs is carried out using the Basin Hopping Monte Carlo approach. Although one of the empirical potentials is found to favour the LT structure, it is shown that Marks Decahedral and mixed FCC-HCP motifs are lowest in energy at the DFT level.

The structures and chemical ordering (segregation properties) of Pd-Pt clusters (1 : 1 compositions for N ¼ 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 ¼ 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 ¼ 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).

Elucidating the interplay between shape, chemical composition and catalytic activity is an essential task in the rational nanocatalyst design process. We investigated the activity of MgO-supported PtNi nanoalloys of ∼1.5 nm towards the oxygen reduction reaction using firstprinciples simulations. Cuboctahedral-shaped particles result to be more active than truncated octahedra of similar sizes and alloying produces a quantitative improvement in the catalytic activity independently of the catalyst morphology. Our results suggest a practical recipe for catalyst nano-engineering controlling the chemical composition at the metal oxide interface. Indeed Ni atoms in contact with the oxide support reduce the binding energy of molecular oxygen at different adsorption sites.