Structural distribution in mixed ternary noble gas and Lennard-Jones clusters

Wu, Xia; Huang, Cuifang; Sun, Yan; Wu, Guangxin

doi:10.1016/j.chemphys.2012.12.024

Cited by 9 publications

(6 citation statements)

References 38 publications

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“…However, other algorithms, such as evolutionary algorithm and basin‐hopping algorithm, are also used as strategies of geometrical improvements. It would be very interesting to apply SGMS‐HMGP to other systems, multicomponent Lennard‐Jones atomic clusters, water clusters, and off‐lattice protein models . These applications are helpful to evaluate the size‐guided multi‐seed algorithm.…”

Section: Discussionmentioning

confidence: 99%

Size‐guided multi‐seed heuristic method for geometry optimization of clusters: Application to benzene clusters

Takeuchi

2018

J Comput Chem

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Since searching for the global minimum on the potential energy surface of a cluster is very difficult, many geometry optimization methods have been proposed, in which initial geometries are randomly generated and subsequently improved with different algorithms. In this study, a size-guided multi-seed heuristic method is developed and applied to benzene clusters. It produces initial configurations of the cluster with n molecules from the lowest-energy configurations of the cluster with n - 1 molecules (seeds). The initial geometries are further optimized with the geometrical perturbations previously used for molecular clusters. These steps are repeated until the size n satisfies a predefined one. The method locates putative global minima of benzene clusters with up to 65 molecules. The performance of the method is discussed using the computational cost, rates to locate the global minima, and energies of initial geometries. © 2018 Wiley Periodicals, Inc.

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Section: Discussionmentioning

confidence: 99%

Size‐guided multi‐seed heuristic method for geometry optimization of clusters: Application to benzene clusters

Takeuchi

2018

J Comput Chem

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“…In these studies, the clusters are defined as follows: (i) l = m = n = 10, 1.0 ≤ S B ≤ 1.3, 1.0 ≤ S C ≤ 1.3 [9]; (ii) N = 9 -55 (l : m : n ≅ 1 : 1: 1), (S B , S C ) = (1.1, 1.2), (1.2, 1.4) [9]; (iii) l = 13, m + n = 42, S B = 1.05, S C = 1.1 [9]; (iv) l = 12, m = n = 13, 1.0 ≤ S B ≤ 1.4, 1.0 ≤ S C ≤ 1.4 [10]. They also calculated the global-minimum structures of noble gas systems of Ar 12 Kr m Xe n (m + n = 26) [10], Ar 13 Kr 11 Xe 11 ) to demonstrate the effects of compositional changes on the structures. In the above studies [9 -12], the atomic compositions are partially or completely fixed and the cluster sizes are rather limited in some cases.…”

Section: Introductionmentioning

confidence: 99%

“…For ternary LJ clusters A l B m C n (N = l + m + n), Wu and coworkers [9,10] examined the effect of the size parameters, σ BB and σ CC (= S C σ), on the global-minimum geometries. In these studies, the clusters are defined as follows: (i) l = m = n = 10, 1.0 ≤ S B ≤ 1.3, 1.0 ≤ S C ≤ 1.3 [9]; (ii) N = 9 -55 (l : m : n ≅ 1 : 1: 1), (S B , S C ) = (1.1, 1.2), (1.2, 1.4) [9]; (iii) l = 13, m + n = 42, S B = 1.05, S C = 1.1 [9]; (iv) l = 12, m = n = 13, 1.0 ≤ S B ≤ 1.4, 1.0 ≤ S C ≤ 1.4 [10].…”

Section: Introductionmentioning

confidence: 99%

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Ternary and quaternary Lennard-Jones atomic clusters: The effects of atomic sizes on the compositions, geometries, and relative stability

Takeuchi

2015

Chemical Physics

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Supplementary data Table S1. The potential energies of the global minima (E N /) of the ternary Lennard-Jones clusters, the number of initial geometries (N ini ), the number of times that the global minimum was obtained (N hit ), the average number of local optimizations in the run (N ls ), and the numbers of the A, B, and C atoms (N A , N B , N C ) in the clusters. For the clusters with N = 5, the atom-type conversion operator yielded the putative global minimum many times and thus the interior and surface operators were not applied to them. For the clusters with N = 6 -7, the maximum numbers of atoms moved by the interior and surface operators were set at N -3 and N -4, respectively. Table S3. The global-minimum geometries of the ternary Lennard-Jones clusters. Table S4. The global-minimum geometries of the quaternary Lennard-Jones clusters.

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“…16 On the other hand, optimization algorithm, such as genetic algorithm (GA) 17,18 and adaptive immune optimization algorithm (AIOA), 19 were also made for optimizing bimetallic and ternary clusters, e.g., Cu-Au, 20 Ag-Pd, AgAu, 21 and Ar-Kr-Xe clusters. 22 In general, the optimization algorithm proposed for binary clusters was originally developed for monoatomic clusters. For instance, GA was previously developed to determine the lowest energy configurations of Lennard-Jones (LJ) 2-100 clusters 23 and MgO clusters bound by a simple Coulomb-plus-Born-Mayer potential.…”

Section: Introductionmentioning

confidence: 99%

Fast optimization of binary clusters using a novel dynamic lattice searching method

Cheng

2014

The Journal of Chemical Physics

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Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd)79 clusters with DFT-fit parameters of Gupta potential.

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Structural distribution in mixed ternary noble gas and Lennard-Jones clusters

Cited by 9 publications

References 38 publications

Size‐guided multi‐seed heuristic method for geometry optimization of clusters: Application to benzene clusters

Size‐guided multi‐seed heuristic method for geometry optimization of clusters: Application to benzene clusters

Ternary and quaternary Lennard-Jones atomic clusters: The effects of atomic sizes on the compositions, geometries, and relative stability

Fast optimization of binary clusters using a novel dynamic lattice searching method

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