Journal ArticleDOI
Investigation of the structures of MgO clusters using a genetic algorithm
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TLDR
In this article, the Coulomb-plus-Born-Mayer potential was used to find the global minima for MgO clusters, and the results of the genetic algorithm search method could be coupled with more accurate calculation methods.Abstract:
The application of a genetic algorithm, for optimizing the geometries of stoichiometric and non-stoichiometric MgO clusters, bound by a simple Coulomb-plus-Born–Mayer potential, is investigated. The genetic algorithm is shown to be efficient and reliable for finding, reproducibly the global minima for these clusters. The variation of the structures of MgO clusters are investigated as a function of the formal charges (±q) on the ions—ranging from q = 1 to q = 2. In agreement with previous studies, lower charges are found to favour compact, rocksalt-like cuboidal clusters, while the higher formal charges favour hollow pseudo-spherical structures. Hexagonal stacks are also found to be stable for small (MgO)N clusters with N = 3n. Comparisons are made with experimental mass spectral
abundances and the results of previous empirical calculations, as well as with more sophisticated model potential and ab initio calculations. Finally, possible ways in which the genetic algorithm search method could be coupled with more accurate calculation methods are discussed.read more
Citations
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Crystal structure prediction from first principles
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TL;DR: The current state of the art in this field is illustrated with topical applications to inorganic, especially microporous solids, and to molecular crystals; the field also looks at applications to nanoparticulate structures.
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Jun Zhang,Michael Dolg +1 more
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Structure and Stability of Small TiO2 Nanoparticles
TL;DR: A computational study that locates the global minima in the potential energy surface of Ti(n)O2n clusters with n = 1-15 and reports novel structures that provide the basis for further computational studies of the effect of nanostructure on adsorption, photochemistry, and nucleation of this material.
Journal ArticleDOI
Genetic algorithms in materials design and processing
TL;DR: Genetic algorithms (GAs) are biologically inspired computing techniques, which tend to mimic the basic Darwinian concepts of natural selection, and are highly robust and efficient for most engineering optimising studies as mentioned in this paper.
Journal ArticleDOI
Global optimization of clusters using electronic structure methods
Sven Heiles,Roy L. Johnston +1 more
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References
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Journal ArticleDOI
Molecular Geometry Optimization with a Genetic Algorithm
D. M. Deaven,Kai-Ming Ho +1 more
TL;DR: This work presents a method for reliably determining the lowest energy structure of an atomic cluster in an arbitrary model potential, based on a genetic algorithm that operates on a population of candidate structures to produce new candidates with lower energies.
Journal ArticleDOI
Global geometry optimization of clusters using genetic algorithms
TL;DR: With the number of potential energy function evaluations as a measure, the genetic algorithm is more economical than either a set of traditional, local minimizations or a molecular dynamics simulated annealing approach.
Journal ArticleDOI
Structural consequences of the range of the interatomic potential A menagerie of clusters
TL;DR: In this paper, the authors attempted to find the global minima of clusters containing between 20 and 80 atoms bound by the Morse potential, as a function of the range of the interatomic force.
Journal ArticleDOI
The Genetic Algorithm: Foundations and Apllications in Structure Solution from Powder Diffraction Data
TL;DR: The fundamental concepts underlying genetic algorithms are discussed and the implementation of the genetic algorithm for structure solution from powder diffraction data is described, with examples of previously known and previously unknown structures.