Jump to main content
Jump to site search

Issue 22, 2003
Previous Article Next Article

Evolving better nanoparticles: Genetic algorithms for optimising cluster geometries

Author affiliations

Abstract

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.

Graphical abstract: Evolving better nanoparticles: Genetic algorithms for optimising cluster geometries

Back to tab navigation

Publication details

The article was received on 21 May 2003, accepted on 15 Aug 2003 and first published on 01 Sep 2003


Article type: Perspective
DOI: 10.1039/B305686D
Citation: Dalton Trans., 2003,0, 4193-4207
  •   Request permissions

    Evolving better nanoparticles: Genetic algorithms for optimising cluster geometries

    R. L. Johnston, Dalton Trans., 2003, 0, 4193
    DOI: 10.1039/B305686D

Search articles by author

Spotlight

Advertisements