Geometry optimization of atomic clusters using a heuristic method with dynamic lattice searching

In this paper, a global optimization method is presented to determine the global-minimum structures of atomic clusters, where several already existing techniques are combined, such as the dynamic lattice searching method and two-phase local minimization method. The present method is applied to some selected large-sized Lennard-Jones (LJ) clusters and silver clusters described by the Gupta potential in the size range N = 13-140 and 300. Comparison with the results reported in the literature shows that the method is highly efficient and a lot of new global minima missed in previous papers are found for the silver clusters. The method may be a promising tool for the theoretical determination of ground-state structure of atomic clusters. Additionally, the stabilities of silver clusters are also analyzed and it is found that in the size range N = 13-140 there exist 12 particularly stable clusters.     

Development of an efficient geometry optimization method for water clusters

A geometry optimization method for water clusters (H(2)O)(n) was developed in the present study. The method was applied to the TIP3P and TIP4P water clusters in the range of n < or = 30, and the resulting structures were compared with the global-minimum structures in the literature (n < or = 25 for the TIP3P potential and n < or = 30 for the TIP4P potential). The method failed to reproduce the previously reported global minimum of the n = 24 TIP4P cluster. However, it was possible to find new global minima for the n = 24, 26-30 TIP3P cluster and the TIP4P clusters of 25, 28, 29, and 30 molecules.     

Geometry optimization of molecular clusters and complexes using scaled internal coordinates

Scaled internal coordinates are introduced for use in the geometry optimization of systems composed of multiple fragments, such as solvated molecules, clusters, and biomolecular complexes. The new coordinates are related to bond lengths, bond angles and torsion angles by geometry-dependent scaling factors. The scaling factors serve to expedite the optimization of complexes containing outlying fragments, without hindering the optimization of the intramolecular degrees of freedom. Trial calculations indicate that, at asymptotic separations, the scaling factors improve the rate of convergence by a factor of 4 to 5.     

Geometry optimization and conformational analysis of (C60)N clusters using a dynamic lattice-searching method.

A newly developed unbiased global optimization method, named dynamic lattice searching (DLS), is used to locate putative global minima for all (C6O)N clusters with Girifalco potential up to N=150. A simple greedy strategy is adopted for the basic frame, so DLS has a very high convergence speed and may converge at various configurations. As most structures are packed by basic tetrahedra, some sequences are defined by both configurations and the size of the basic tetrahedra. A sequence-based conformational analysis is carried out with the defined sequences by counting the hit number over 10,000 independent DLS runs for all the cases up to N = 5. It was found that the hit rate of a sequence is related to the size of the basic tetrahedra. U.e of this method proved that the Leary tetrahedral sequence is dominant in a certain range of cluster sizes, although the sequence has no potential energy advantage. The calculation results are also consistent with those of annealing experiments at high temperature, both in magic numbers and height of the peaks in the mass spectrum.     

Geometry optimization using symmetry coordinates

The use of symmetry coordinates (SC ) in geometry optimization is discussed. A computer program incorporating the use of sc, together with analytical calculation of the gradient and quadratic acceleration, is described. Also reported are careful test results on a series of small molecules and typical results with a long series of molecules up to quite large size (40–60 atoms).     

Structures of bimetallic clusters

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.     

Reactivity and stability of bimetallic clusters

Using two independent vaporization lasers, bimetallic clusters composed of transition elements and A1 were generated by the laser vaporization method. Reactivity toward hydrogen adsorption of bimetallic clusters was compared with genuine clusters. It was found that A1 which has no reactivity toward hydrogen plays a role of either inhibitor or accelerator of the reaction when A1 is mixed with Nb or Co. Unusual stability of Co₁₂ V₁ in contrast to the high reactivity of Co_12–13 is attributed to the rigid geometric structure where V occupies the central position.     

Geometry optimizations of benzene clusters using a modified genetic algorithm

A modified genetic algorithm with real-number coding, non-uniform mutation and arithmetical crossover operators was described in this paper. A local minimization was used to improve the final solution obtained by the genetic algorithm. Using the exp-6-1 interatomic energy function, the modified genetic algorithm with local minimization (MGALM) was applied to the geometry optimization problem of small benzene clusters (C6H6)N(N = 2-7) to obtain the global minimum energy structures. MGALM is simple but the structures optimized are comparable to the published results obtained by parallel genetic algorithms.     

Geometry optimization of periodic systems using internal coordinates

An algorithm is proposed for the structural optimization of periodic systems in internal (chemical) coordinates. Internal coordinates may include in addition to the usual bond lengths, bond angles, out-of-plane and dihedral angles, various "lattice internal coordinates" such as cell edge lengths, cell angles, cell volume, etc. The coordinate transformations between Cartesian (or fractional) and internal coordinates are performed by a generalized Wilson B-matrix, which in contrast to the previous formulation by Kudin et al. [J. Chem. Phys. 114, 2919 (2001)] includes the explicit dependence of the lattice parameters on the positions of all unit cell atoms. The performance of the method, including constrained optimizations, is demonstrated on several examples, such as layered and microporous materials (gibbsite and chabazite) as well as the urea molecular crystal. The calculations used energies and forces from the ab initio density functional theory plane wave method in the projector-augmented wave formalism.     

Optimization of bimetallic Cu–Au and Ag–Au clusters by using a modified adaptive immune optimization algorithm

A modified adaptive immune optimization algorithm (AIOA) is designed for optimization of Cu–Au and Ag–Au bimetallic clusters with Gupta potential. Compared with homoatom clusters, there are homotopic isomers in bimetallic cluster, so atom exchange operation is presented in the modified AIOA. The efficiency of the algorithm is tested by optimization of Cu_nAu_38‐n (0 ≤ n ≤ 38). Results show that all the structures with the putative global minimal energies are successfully located. In the optimization of Ag_nAu_55‐n (0 ≤ n ≤ 55) bimetallic clusters, all the structures with the reported minimal energies are obtained, and 36 structures with even lower potential energies are found. On the other hand, with the optimized structures of Cu_nAu_55‐n, it is shown that all 55‐atom Cu–Au bimetallic clusters are Mackay icosahedra except for Au₅₅, which is a face‐centered cubic (fcc)‐like structure; Cu₅₅, Cu₁₂Au₄₃, and Cu₁Au₅₄ have two‐shell Mackay icosahedral geometries with I_h point group symmetry. © 2009 Wiley Periodicals, Inc. J Comput Chem 2009     

Geometry optimization using generalized, chemically meaningful constraints

An external geometry optimizer (BOptimize) is described that can be used together with a number of existing quantum-chemical codes (Gaussian, Gamess-UK, Turbomole, ADF, Orca, Priroda, Spartan-PM3, Mopac) and allows flexible and general constrained optimizations. Some details of the implementation are discussed, and examples are provided of constrained optimizations that would be difficult or impossible to perform with existing optimizers.     

Global optimization of atomic and molecular clusters using the space-fixed modified genetic algorithm method

A modified genetic algorithm approach has been applied to atomic Ar clusters and molecular water clusters up to (H₂O)₁₃. Several genetic operators are discussed which are suitable for real-valued space-fixed atomic coordinates and Euler angles. The performance of these operators has been systematically investigated. For atomic systems, it is found that a mix of operators containing a coordinate-averaging operator is optimal. For angular coordinates, the situation is less clear. It appears that inversion and two-point crossover operators are the best choice. © 1997 John Wiley & Sons, Inc. J Comput Chem 18: 1233–1244     

Global optimization of clusters using electronic structure methods

Over the past decade, there has been a significant growth in the development and application of methods for performing global optimization (GO) of cluster and nanoparticle structures using first‐principles electronic structure methods coupled to sophisticated search algorithms. This has in part been driven by the desire to avoid the use of empirical potentials (EPs), especially in cases where no reliable potentials exist to guide the search toward reasonable regions of configuration space. This has been facilitated by improvements in the reliability of the search algorithms, increased efficiency of the electronic structure methods, and the development of faster, multiprocessor high‐performance computing architectures. In this review, we give a brief overview of GO algorithms, though concentrating mainly on genetic algorithm and basin hopping techniques, first in combination with EPs. The major part of the review then deals with details of the implementation and application of these search methods to allow exploration for global minimum cluster structures directly using electronic structure methods and, in particular, density functional theory. Example applications are presented, ranging from isolated monometallic and bimetallic clusters to molecular clusters and ligated and surface supported metal clusters. Finally, some possible future developments are highlighted. © 2013 Wiley Periodicals, Inc.     

Novel method for geometry optimization of molecular clusters: application to benzene clusters

A heuristic and unbiased method for searching optimal geometries of clusters of nonspherical molecules was constructed from the algorithm recently proposed for Lennard-Jones atomic clusters. In the method, global minima are searched by using three operators, interior, surface, and orientation operators. The first operator gives a perturbation on a cluster configuration by moving molecules near the center of mass of a cluster, and the second one modifies a cluster configuration by moving molecules to the most stable positions on the surface of a cluster. The moved molecules are selected by employing a contribution of the molecules to the potential energy of a cluster. The third operator randomly changes the orientations of all molecules. The proposed method was applied to benzene clusters. It was possible to find new global minima for (C6H6)11, (C6H6)14, and (C6H6)15. Global minima for (C6H6)16 to (C6H6)30 are first reported in this article.     

Many-body optimization using an ab initio monte carlo method

Advances in computing power have made it possible to study solvated molecules using ab initio quantum chemistry. Inclusion of discrete solvent molecules is required to determine geometric information about solute/solvent clusters. Monte Carlo methods are well suited to finding minima in many-body systems, and ab initio methods are applicable to the widest range of systems. A first principles Monte Carlo (FPMC) method was developed to find minima in many-body systems, and emphasis was placed on implementing moves that increase the likelihood of finding minimum energy structures. Partial optimization and molecular interchange moves aid in finding minima and overcome the incomplete sampling that is unavoidable when using ab initio methods. FPMC was validated by studying the boron trifluoride-water system, and then the method was used to examine the methyl carbenium ion in water to demonstrate its application to solvation problems.     

Structural and energetic properties of Ni-Cu bimetallic clusters

The lowest-energy structures for all compositions of Ni n Cu m bimetallic clusters with N = n + m up to 20 atoms, N = 23, and N = 38 atoms have been determined using a genetic algorithm for unbiased structure optimization in combination with an embedded-atom method for the calculation of the total energy for a given structure. Comparing bimetallic clusters with homoatomic clusters of the same size, it is shown that the most stable structures for each cluster size are composed entirely of Ni atoms. Among the bimetallic clusters in the size range N = 2-20, the Ni N-1 Cu 1 clusters possess the highest stability. Further, it has been established that most of the bimetallic cluster structures have geometries similar to those of pure Ni clusters. The size N = 38 presents a special case, as the bimetallic clusters undergo a dramatic structural change with increasing atom fraction of Cu. Moreover, we have identified an icosahedron, a double, and a triple icosahedron with one, two, and three Ni atoms at the centers, respectively, as particularly stable structures. We show that in all global-minimum structures Ni atoms tend to occupy mainly high-coordination inner sites, and we confirm the segregation of Cu on the surface of Ni-Cu bimetallic clusters predicted in previous studies. Finally, it is observed that, in contrast to the bulk, the ground-state structures of the 15-, 16-, and 17-atom bimetallic clusters do not experience a smooth transition between the structures of the pure copper and the pure nickel clusters as a function of the relative number of the two types of atoms. For these sizes, the concentration effect on energy is more important than the geometric one.     

Phase diagram of complex fluids using an efficient integral equation method

We present an adaptive technique for the determination of the phase diagram of fluids within the integral equation theory. It enables an efficient and accurate systematic mapping of the thermodynamic space in order to construct the binodal and spinodal lines. Results are obtained with the thermodynamically consistent integral equation proposed by Sarkisov [J. Chem. Phys. 114, 9496 (2001)] within the tangent linear technique that yields an exact differentiation of correlation functions. The generality of the numerical approach is assessed by determining both the liquid-vapor coexistence and the critical parameters of the generalized Lennard-Jones (n,6) potentials with varying repulsive part, including the hard-sphere limit.     

Clever and efficient method for searching optimal geometries of lennard-jones clusters

An unbiased algorithm for determining global minima of Lennard-Jones (LJ) clusters is proposed in the present study. In the algorithm, a global minimum is searched by using two operators: one modifies a cluster configuration by moving atoms to the most stable positions on the surface of a cluster and the other gives a perturbation on a cluster configuration by moving atoms near the center of mass of a cluster. The moved atoms are selected by employing contribution of the atoms to the potential energy of a cluster. It was possible to find new global minima for LJ506, LJ521, LJ536, LJ537, LJ538, and LJ541 together with putative global minima of LJ clusters of 10-561 atoms reported in the literature. This indicates that the present method is clever and efficient for cluster geometry optimization.