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The international journal for inorganic, organometallic and bioinorganic chemistry
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Perspective
Dalton Trans., 2003, 4193 - 4207, DOI: 10.1039/b305686d
Evolving better nanoparticles: Genetic algorithms for optimising cluster geometries
Roy L. Johnston
A review is presented of the design and application of genetic algorithms for the geometry optimisation of clusters and nanoparticles, where the interactions between atoms, ions or molecules are described by a variety of potential energy functions. A general introduction to genetic algorithms is followed by a detailed description of the genetic algorithm program that we have developed to identify the lowest energy isomers for a variety of atomic and molecular clusters. Examples are presented of its application to model Morse clusters, ionic MgO clusters and bimetallic
nanoalloy
clusters. Finally, a number of recent innovations and possible future developments are discussed.
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