DFT global optimisation of gas-phase and MgO-supported sub-nanometre AuPd clusters.

The Birmingham Parallel Genetic Algorithm (BPGA) has been adopted for the global optimization of free and MgO(100)-supported Pd, Au and AuPd nanocluster structures, over the size range N = 4-10. Structures were evaluated directly using density functional theory, which has allowed the identification of Pd, Au and AuPd global minima. The energetics, structures, and tendency of segregation have been evaluated by different stability criteria such as binding energy, excess energy, second difference in energy, and adsorption energy. The ability of the approach in searching for putative global minimum has been assessed against a systematic homotop search method, which shows a high degree of success.

A comparative study of AumRhn (4 ≤ m + n ≤ 6) clusters in the gas phase versus those deposited on (100) MgO.

A comparative theoretical study has been performed of the gas phase and deposited AumRhn (4 ≤ m + n ≤ 6) clusters. The combined use of a genetic algorithm and Density Functional Theory (DFT) calculations allows us to explore the potential energy surface and, therefore, find efficiently and automatically the global minimum configuration for each composition. Our results show interesting effects on the geometries of the clusters on deposition. This occurs because the rhodium atoms (electronically) prefer to be in contact with the MgO surface, sometimes promoting planar clusters to become three-dimensional when deposited, and three-dimensional clusters in the gas phase to become two-dimensional. Together with the change in geometries, the magnetic moment is reduced from the gas phase, as the electrons rearrange themselves when the cluster interacts with the substrate.

Global optimization of small bimetallic Pd-Co binary nanoalloy clusters: a genetic algorithm approach at the DFT level.

The global optimisation of small bimetallic PdCo binary nanoalloys are systematically investigated using the Birmingham Cluster Genetic Algorithm (BCGA). The effect of size and composition on the structures, stability, magnetic and electronic properties including the binding energies, second finite difference energies and mixing energies of Pd-Co binary nanoalloys are discussed. A detailed analysis of Pd-Co structural motifs and segregation effects is also presented. The maximal mixing energy corresponds to Pd atom compositions for which the number of mixed Pd-Co bonds is maximised. Global minimum clusters are distinguished from transition states by vibrational frequency analysis. HOMO-LUMO gap, electric dipole moment and vibrational frequency analyses are made to enable correlation with future experiments.

The Effect of Dispersion Correction on the Adsorption of CO on Metallic Nanoparticles.

The effect of dispersion corrections at a range of theory levels on the chemisorption properties of metallic nanoparticles is presented. The site preference for CO on Pt, Au, Pd, and Ir nanoparticles is determined for two geometries, the 38-atom truncated octahedron and the 55-atom icosahedron using density functional theory (DFT). The effects of Grimme's DFT-D2 and DFT-D3 corrections and the optPBE vdW-DF on the site preference of CO is then compared to the "standard" DFT results. Functional behavior is shown to depend not only on the metal but also on the geometry of the nanoparticle with significant effects seen for Pt and Au. There are both qualitative and quantitative differences between the functionals, with significant energetic differences in the chemical ordering of inequivalent sites and adsorption energies varying by up to 1.6 eV.

The Birmingham parallel genetic algorithm and its application to the direct DFT global optimisation of Ir(N) (N = 10-20) clusters.

A new open-source parallel genetic algorithm, the Birmingham parallel genetic algorithm, is introduced for the direct density functional theory global optimisation of metallic nanoparticles. The program utilises a pool genetic algorithm methodology for the efficient use of massively parallel computational resources. The scaling capability of the Birmingham parallel genetic algorithm is demonstrated through its application to the global optimisation of iridium clusters with 10 to 20 atoms, a catalytically important system with interesting size-specific effects. This is the first study of its type on Iridium clusters of this size and the parallel algorithm is shown to be capable of scaling beyond previous size restrictions and accurately characterising the structures of these larger system sizes. By globally optimising the system directly at the density functional level of theory, the code captures the cubic structures commonly found in sub-nanometre sized Ir clusters.

Comparative modelling of chemical ordering in palladium-iridium nanoalloys.

Chemical ordering in "magic-number" palladium-iridium nanoalloys has been studied by means of density functional theory (DFT) computations, and compared to those obtained by the Free Energy Concentration Expansion Method (FCEM) using derived coordination dependent bond energy variations (CBEV), and by the Birmingham Cluster Genetic Algorithm using the Gupta potential. Several compositions have been studied for 38- and 79-atom particles as well as the site preference for a single Ir dopant atom in the 201-atom truncated octahedron (TO). The 79- and 38-atom nanoalloy homotops predicted for the TO by the FCEM/CBEV are shown to be, respectively, the global minima and competitive low energy minima. Significant reordering of minima predicted by the Gupta potential is seen after reoptimisation at the DFT level.

Global optimization of 8-10 atom palladium-iridium nanoalloys at the DFT level.

The global optimization of PdnIr(N-n) N = 8-10 clusters has been performed using the Birmingham Cluster Genetic Algorithm (BCGA). Structures were evaluated directly using density functional theory (DFT), which has allowed the identification of Ir and Ir-rich PdIr cubic global minima, displaying a strong tendency to segregate. The ability of the searches to find the putative global minimum has been assessed using a homotop search method, which shows a high degree of success. The role of spin in the system has been considered through a series of spin-restricted reoptimizations of BCGA-DFT minima. The preferred spin of the clusters is found to vary widely with composition, showing no overall trend in lowest-energy multiplicities.