Surveying a potential energy surface by eigenvector-following

We have developed a method to search potential energy surfaces which avoids some of the difficulties associated with trapping in local minima. Steps are directly taken between minima using eigenvector-following. Exploration of this space by low temperature Metropolis Monte Carlo is a useful global optimisation tool. This method successfully finds the lowest energy icosahedral minima of Lennard- Jones clusters from random starting configurations, but cannot find the global minimum in a reasonable time for difficult cases such as the 38-atom Lennard-Jones cluster where the face-centred-cubic truncated octahedron is lowest in energy. However, by performing searches at higher temperatures, we have found a pathway between the truncated octahedron and the lowest energy icosahedral minima. Such a pathway may be illustrative of some of the structural transformations that are observed for supported metal clusters by electron microscopy.     

An evolutionary algorithm for the global optimization of molecular clusters: application to water, benzene, and benzene cation

We have developed an evolutionary algorithm (EA) for the global minimum search of molecular clusters. The EA is able to discover all the putative global minima of water clusters up to (H(2)O)(20) and benzene clusters up to (C(6)H(6))(30). Then, the EA was applied to search for the global minima structures of (C(6)H(6))(n)(+) with n = 2-20, some of which were theoretically studied for the first time. Our results for n = 2-6 are consistent with previous theoretical work that uses a similar interaction potential. Excluding the very symmetric global minimum structure for n = 9, the growth pattern of (C(6)H(6))(n)(+) with n ≥ 7 involves the (C(6)H(6))(2)(+) dimer motif, which is placed off-center in the cluster. Such observation indicates that potentials commonly used in the literature for (C(6)H(6))(n)(+) cannot reproduce the icosahedral-type packing suggested by the available experimental data.     

On the use of different potential energy functions in rare-gas cluster optimization by genetic algorithms: application to argon clusters

We study the effect of the potential energy function on the global minimum structures of argon clusters arising in the optimization performed by genetic algorithms (GAs). We propose a robust and efficient GA which allows for the calculation of all of the putative global minima of Ar(N) (N = 3-78) clusters modeled with four different potentials. Both energetic and structural properties of such minima are compared among each other and with those previously obtained for the Lennard-Jones function. In addition, the possibility of obtaining global minima of one potential through local optimization over the corresponding cluster geometry given by other potentials was associated with some structural parameters. The influence of the contribution from the three-body (Axilrod-Teller-Muto) triple-dipole potential (including or not a damping function to describe its correct behavior at smaller interatomic distances) has also been analyzed.     

Structural study of gold clusters

Density functional theory (DFT) calculations were carried out to study gold clusters of up to 55 atoms. Between the linear and zigzag monoatomic Au nanowires, the zigzag nanowires were found to be more stable. Furthermore, the linear Au nanowires of up to 2 nm are formed by slightly stretched Au dimers. These suggest that a substantial Peierls distortion exists in those structures. Planar geometries of Au clusters were found to be the global minima till the cluster size of 13. A quantitative correlation is provided between various properties of Au clusters and the structure and size. The relative stability of selected clusters was also estimated by the Sutton-Chen potential, and the result disagrees with that obtained from the DFT calculations. This suggests that a modification of the Sutton-Chen potential has to be made, such as obtaining new parameters, in order to use it to search the global minima for bigger Au clusters.     

Clusters containing open-shell molecules: minimum-energy structures and low-lying isomers of ArnCH (X 2 pi), n = 1 to 15

The size evolution of the equilibrium structures of open-shell ArnCH (X 2 pi) Van der Waals clusters is investigated for n = 1 to 15. We describe a method for combining pair potentials for Ar-CH and Ar-Ar interactions to obtain potential energy surfaces for ArnCH clusters. For each cluster size considered, the global and a few energetically close local minima are calculated using simulated annealing followed by a direct minimization scheme. Ar2CH is found to have an unusually stable planar structure, which persists as a motif in larger ArnCH clusters and has a strong effect on their optimal geometries. The lowest-energy isomers of ArnCH with n = 3 to 11 have all Ar atoms in a shell around CH. The only exception is Ar4CH, where the fully solvated isomer is 3 cm-1 higher in energy than the optimal isomer with CH bound to the surface of the Ar4 tetrahedron. For n = 7 to 11, the minimum-energy structure of ArnCH derives from the global minimum of the Arn + 1 cluster, by replacing the Ar atom at the bottom of the pentagonal bipyramid with CH. The lowest-energy structure of Ar12CH is that of the optimal icosahedral Ar13 cluster, with CH replacing one of the Ar atoms on the cluster surface. This structure supports the proposition based on the spectroscopic data, that for ArnCH clusters with about 10 to 50 Ar atoms CH resides on the surface of Arn.     

Novel structural motifs in clusters of dipolar spheres: knots, links, and coils

We present the structures of putative global potential energy minima for clusters bound by the Stockmayer (Lennard-Jones plus point dipole) potential. A rich variety of structures is revealed as the cluster size and dipole strength are varied. Most remarkable are groups of closed-loop structures with the topology of knots and links. Despite the large number of possibilities, energetically optimal structures exhibit only a few such topologies.     

(SiO2)n团簇的基态能量和结构

应用遗传算法对二氧化硅团簇（SiO2）n（n≤20）的结构进行了优化计算。分析讨论了结构和结合能随团簇尺寸的变化规律,发现（SiO2）n团簇系列不存在明显的幻数,并在n≤20的范围内,不呈现出相应大块物质的结构特征,     

A strategy to find minimal energy nanocluster structures

An unbiased strategy to search for the global and local minimal energy structures of free standing nanoclusters is presented. Our objectives are twofold: to find a diverse set of low lying local minima, as well as the global minimum. To do so, we use massively the fast inertial relaxation engine algorithm as an efficient local minimizer. This procedure turns out to be quite efficient to reach the global minimum, and also most of the local minima. We test the method with the Lennard–Jones (LJ) potential, for which an abundant literature does exist, and obtain novel results, which include a new local minimum for LJ₁₃, 10 new local minima for LJ₁₄, and thousands of new local minima for . Insights on how to choose the initial configurations, analyzing the effectiveness of the method in reaching low‐energy structures, including the global minimum, are developed as a function of the number of atoms of the cluster. Also, a novel characterization of the potential energy surface, analyzing properties of the local minima basins, is provided. The procedure constitutes a promising tool to generate a diverse set of cluster conformations, both two‐ and three‐dimensional, that can be used as an input for refinement by means of ab initio methods. © 2013 Wiley Periodicals, Inc.     

Monte Carlo temperature basin paving with effective fragment potential: an efficient and fast method for finding low-energy structures of water clusters (H2O)20 and (H2O)25

Determining low-energy structures of large water clusters is a challenge for any optimization algorithm. In this work, we have developed a new Monte Carlo (MC)-based method, temperature basin paving (TBP), which is related to the well-known basin hopping method. In the TBP method, the Boltzmann weight factor used in MC methods is dynamically modified based on the history of the simulation. The states that are visited more are given a lower probability by increasing their temperatures and vice versa. This allows faster escapes from the states frequently visited in the simulation. We have used the TBP method to find a large number of low-energy minima of water clusters of size 20 and 25. We have found structures energetically same to the global minimum structures known for these two clusters. We have compared the efficiency of this method to the basin-hopping method and found that it can locate the minima faster. Statistical efficiency of the new method has been investigated by running a large number of trajectories. The new method can locate low-energy structures of both the clusters faster than some of the reported algorithms for water clusters and can switch between high energy and low-energy structures multiple times in a simulation illustrating its efficiency. The large number of minima obtained from the simulations is used to get both general and specific features of the minima. The distribution of minima for these two clusters based on the similarity of their oxygen frames shows that the (H(2)O)(20) can have different variety of structures, but for (H(2)O)(25), low-energy structures are mostly cagelike. Several (H(2)O)(25) structures are found with similar energy but with different cage architectures. Noncage structures of (H(2)O)(25) are also found but they are 6-7 kcal/mol higher in energy from the global minimum. The TBP method is likely to play an important role for exploring the complex energy landscape of large molecules.     

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.     

A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters

In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing.     

More on the melting of Lennard-Jones clusters

The melting of 13-atom clusters interacting via Lennard-Jones potentials has been revisited using molecular dynamics coupled to steepest descent quenches. A procedure was devised to account for the fraction of times the global and local minima of the potential energy surface are accessed during a long trajectory. This quantity presents a sigmoid shape. A phenomenological model of melting is given in terms of a correlated walk that maps the short time excursions among the global and local minima in configuration space. Comparison between the simulation results and the theoretical model shows that the melting transition is well described in terms of the temperature changes of the fraction of high energy minima accessed during the cluster trajectory. Cooperativity is clear from the S shape of this quantity, i.e., the access to a local minimum favours the access to other local minima.     

Atomistic and electronic structure of bimetallic cobalt/rhenium clusters from density functional theory calculations

We have carried out computational density functional investigations of Co I Re J (J=0,1,2; I+J=14) metal atom clusters. Through thorough optimization of geometry, spin polarization, and electronic configuration, the most stable structures for each cluster have been identified. While the global minima are found to be well defined and energetically well separated from other local minima, the study reveals a plethora of different structures and symmetries only moderately higher in energy. A key point of interest is the effect of doping the cobalt clusters with rhenium. Aside from significant structural reorganizations, rhenium is found to stabilize the clusters and couple down the spin. Furthermore, the most stable clusters comprise highly coordinated rhenium and, in the case of Co 12 Re 2, Re-Re bonding. Our results are compared to earlier experimental and computational data.     

Conformational search of peptides and proteins: Monte Carlo minimization with an adaptive bias method applied to the heptapeptide deltorphin

The energy function of a protein consists of a tremendous number of minima. Locating the global energy minimum (GEM) structure, which corresponds approximately to the native structure, is a severe problem in global optimization. Recently we have proposed a conformational search technique based on the Monte Carlo minimization (MCM) method of Li and Scheraga, where trial dihedral angles are not selected at random within the range [-180 degrees,180 degrees ] (as with MCM) but with biased probabilities depending on the increased structure-energy correlations as the GEM is approached during the search. This method, called the Monte Carlo minimization with an adaptive bias (MCMAB), was applied initially to the pentapeptide Leu-enkephalin. Here we study its properties further by applying it to the larger peptide with bulky side chains, deltorphin (H-Tyr-D-Met-Phe-His-Leu-Met-Asp-NH(2)). We find that on average the number of energy minimizations required by MCMAB to locate the GEM for the first time is smaller by a factor of approximately three than the number required by MCM-in accord with results obtained for Leu-enkephalin.     

Lowest-energy structures of (C60)nX (X=Li+,Na+,K+,Cl-) and (C60)nYCl (Y=Li,Na,K) clusters for n</=13

Basin-hopping global optimization is used to find likely candidates for the lowest minima on the potential energy surface of (C(60))(n)X (X=Li(+),Na(+),K(+),Cl(-)) and (C(60))(n)YCl (Y=Li,Na,K) clusters with n相似文献   

Global minimum structures of morse clusters as a function of the range of the potential: 81<or=N<or=160

We have attempted to find the putative global minimum structures of Morse clusters for cluster size N=81-160 as a function of the range of the potential (with potential range rho0>or=3.0). Moreover, compared to the results for N相似文献   

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.     

Protein structure prediction using a combination of sequence homology and global energy minimization I. Global energy minimization of surface loops

A procedure has been developed for global energy minimization of surface loops of proteins in the presence of a fixed core. The ECEPP potential function has been modified to allow more accurate representations of hydrogen bond interactions and intrinsic torsional energies. A computationally efficient representation of hydration free energy has been introduced. A local minimization procedure has been developed that uses a cutoff distance, minimization with respect to subsets of degrees of freedom, analytical second derivatives, and distance constraints between rigid segments to achieve efficiency in applications to surface loops. Efficient procedures have been developed for deforming segments of the initial backbone structure and for removing overlaps. Global energy minimization of a surface loop is accomplished by generating a sequence (or a trajectory) of local minima, the component steps of which are generated by searching collections of local minima obtained by deforming seven-residue segments of the surface loop. The search at each component step consists of the following calculations: (1) A large collection of backbone structures is generated by deforming a seven-residue segment of the initial backbone structure. (2) A collection of low-energy backbone structures is generated by applying local energy minimization to the resulting collection of backbone structures (interactions involving side chains that will be searched in this component step are not included in the energy). (3) One low-energy side-chain structure is generated for each of the resulting low-energy backbone structures. (4) A collection of low-energy local minima is generated by applying local energy minimization to the resulting collection of structures. (5) The local minimum with the lowest energy is retained as the next point of the trajectory. Applications of our global search procedure to surface segments of bovine pancreatic trypsin inhibitor (BPTI) and bovine trypsin suggest that component-step searches are reasonably complete. The computational efficiency of component-step searches is such that trajectories consisting of about 10 component steps are feasible using an FPS-5200 array processor. Our procedure for global energy minimization of surface loops is being used to identify and correct problems with the potential function and to calculate protein structure using a combination of sequence homology and global energy minimization.     

Global optimization of ionic Mg(n)F(2n) (n=1-30) clusters

The global optimization basin-hopping (BH) method has been used to locate the global minima (GM) of Mg(n)F(2n) (n=1-30) clusters using a Born-Mayer-type potential. Some of the GM were particularly difficult to find, requiring more than 1.5 x 10(4) BH steps. We have found that both the binding energy per MgF2 unit and the effective volume of the GM isomers increase almost linearly with n, and that cluster symmetry decreases with cluster size. The data derived from the BH runs reveal a growing density of local minima just above the GM as n increases. Despite this, the attraction basin around each GM is relatively large, since after all their atomic coordinates are randomly displaced by values as high as 2.0 bohrs, the perturbed structures, upon reoptimization, relax back to the GM in more than 50% of the cases (except for n=10 and 11). The relative stabilities derived from energy second differences suggest that n=8,10,13,15, and 20 are probably the magic numbers for these systems. Mass spectrum experiments would be very useful to clarify this issue.     

An unbiased population-based search for the geometry optimization of Lennard-Jones clusters: 2 < or = N < or = 372

This article presents the results obtained using an unbiased Population Based Search (PBS) for optimizing Lennard-Jones clusters. PBS is able to repeatedly obtain all putative global minima, for Lennard-Jones clusters in the range 2 < or = N < or = 372, as reported in the Cambridge Cluster Database. The PBS algorithm incorporates and extends key techniques that have been developed in other Lennard-Jones optimization algorithms over the last decade. Of particular importance are the use of cut-and-paste operators, structure niching (using the cluster strain energy as a metric), two-phase local search, and a new operator, Directed Optimization, which extends the previous concept of directed mutation. In addition, PBS is able to operate in a parallel mode for optimizing larger clusters.