We report an optimization algorithm for studying bimetallic nanoclusters. The algorithm combines two state-of-the-art methods, the genetic algorithm and the basin hopping approach, widely employed in the literature for predicting structures of pure metallic and nonmetallic clusters. To critically test the present algorithm and its use in determining the lowest-energy structures of bimetallic nanoclusters, we apply it to study the bimetallic clusters Cu(n)Au(38-n) (0< or =n< or =38). It is predicted that the Au atoms, being larger in size than the Cu atoms, prefer to occupy surface sites showing thus the segregating behavior. As the atom fraction of Cu increases, the bimetallic cluster Cu(n)Au(38-n), as a whole, first takes on an amorphous structure and is followed by dramatic changes in structure with the Cu atoms revealing hexagonal, then assuming pentagonal, and finally shifting to octahedral symmetry in the Cu-rich range.

A fine Au powder, with a mean particle diameter of 4 nm, has been successfully fabricated. The crystalline structure of the 4 nm Au nanoparticles remains in fcc symmetry. No structural changes were found between 15 and 450 K. A crossover from a positive thermal expansion at low temperatures to a negative thermal expansion at high temperatures was observed in the fcc cell parameter at about 125 K. Anomalies associated with the crossover were also observed in the magnetic response and the heat capacity measurements. The observations can be reasonably well interpreted by accounting for the effects of the valence electron potential on the equilibrium lattice separations, with a weakly temperature dependent level spacing.

The multicanonical basin hopping (MUBH) method, which uses a multicanonical weight in the basin hopping (BH) Monte Carlo method, was found to be very efficient for global optimization of large-scale systems such as Lennard-Jones clusters containing more than 150 atoms. We have implemented an asynchronous parallel version of the MUBH method using the message passing interface (MPI) to take advantage of the full usage of multiprocessors in either a homogeneous or heterogeneous computational environment. Based on the intrinsic properties of the Monte Carlo method, this MPI implementation used the task parallelism to minimize interthread data communication. For a Co nanocluster consisting of N atoms, we have applied the asynchronous multicanonical basin hopping (AMUBH) method (for 181 < N < or = 200), together with BH (for 2 < or = N < 150) and MUBH (for 150 < or = N < or = 180), to search for the molecular configuration of the global energy minimum. AMUBH becomes the only practical computational scheme for locating the energy minimum within realistic computational time for a relatively large cluster.

In this work, we present modifications to the well-known basin hopping (BH) optimization algorithm [D. J. Wales and J. P. Doye, J. Phys. Chem. A 101, 5111 (1997)] by incorporating in it the unique and specific nature of interactions among valence electrons and ions in carbon atoms through calculating the cluster's total energy by the density functional tight-binding (DFTB) theory, using it to find the lowest energy structures of carbon clusters and, from these optimized atomic and electronic structures, studying their varied forms of topological transitions, which include a linear chain, a monocyclic to a polycyclic ring, and a fullerene/cage-like geometry. In this modified BH (MBH) algorithm, we define a spatial volume within which the cluster's lowest energy structure is to be searched, and introduce in addition a cut-and-splice genetic operator to increase the searching performance of the energy minimum than the original BH technique. The present MBH/DFTB algorithm is, therefore, characteristically distinguishable from the original BH technique commonly applied to nonmetallic and metallic clusters, technically more thorough and natural in describing the intricate couplings between valence electrons and ions in a carbon cluster, and thus theoretically sound in putting these two charged components on an equal footing. The proposed modified minimization algorithm should be more appropriate, accurate, and precise in the description of a carbon cluster. We evaluate the present algorithm, its energy-minimum searching in particular, by its optimization robustness. Specifically, we first check the MBH/DFTB technique for two representative carbon clusters of larger size, i.e., C60 and C72 against the popular cut-and-splice approach [D. M. Deaven and K. M. Ho, Phys. Rev. Lett. 75, 288 (1995)] that normally is combined with the genetic algorithm method for finding the cluster's energy minimum, before employing it to investigate carbon clusters in the size range C3-C24 studying their topological transitions. An effort was also made to compare our MBH/DFTB and its re-optimized results carried out by full density functional theory (DFT) calculations with some early DFT-based studies.

We present detailed numerical results on the ground state structures of metallic clusters. The Gupta-type many-body potential is used to account for the interactions between atoms in the cluster. Both the genetic algorithm technique and the basin hopping method have been applied to search for the global energy minima of clusters. The excellent agreement found in both schemes for the global energy minima gives credence to the optimized energy values obtained. For four monovalent and one polyvalent metals studied in this work and within the accuracy of the energies presented here, we find that the global energy minima predicted by the basin hopping method are the same as those values obtained by the genetic algorithm. Our calculations for the ground state energies of alkali metallic clusters show regularities in the energy differences, and the cluster growth pattern manifested by this same group of clusters is generally icosahedral, which is quite different from the close-packed and decahedral preferentially exhibited by the tetravalent lead clusters. Considering the inherent disparities in the electronic properties and the bulk structures in these metals (body-centered cubic for alkali metals and face-centered cubic for the lead metal), it is not unreasonable to conjecture that the valence electrons do play a subtle role in the conformation of metallic clusters.