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Related Experiment Videos

Geometry optimisation of aluminium clusters using a genetic algorithm.

Lesley D Lloyd1, Roy L Johnston, Christopher Roberts

  • 1School of Chemical Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.

Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry
|December 6, 2002
PubMed
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A Genetic Algorithm optimized aluminium cluster geometries (21-55 atoms). It identified various structures, including hollow icosahedral shells, revealing how optimal structures evolve over generations.

Area of Science:

  • Computational Chemistry
  • Materials Science
  • Condensed Matter Physics

Background:

  • Understanding the geometric structure of atomic clusters is crucial for predicting their properties.
  • The behavior of small metallic clusters is complex and not fully understood.
  • Accurate interatomic potentials are needed to model cluster energies and structures.

Purpose of the Study:

  • To optimize the geometry of aluminium clusters containing 21-55 atoms using a Genetic Algorithm.
  • To identify and characterize the stable structural motifs within this size range.
  • To visualize the evolutionary process of structure optimization.

Main Methods:

  • Application of a Genetic Algorithm (GA) for structure optimization.
  • Utilizing the many-body Murrell-Mottram potential to describe interatomic interactions.

Related Experiment Videos

  • Analysis of structural motifs including face-centered cubic, hexagonal close-packed, decahedral, and icosahedral.

    • Main Results:

    • Identification of diverse structural motifs in aluminium clusters (21-55 atoms).
    • Observation of hollow icosahedral shells in larger clusters, with Al55 exhibiting a centered icosahedral structure.
    • Evolutionary Progress Plots demonstrated the step-by-step development of optimal structures for Al19 and Al38.

    Conclusions:

    • Genetic Algorithms are effective for optimizing the geometry of metallic clusters.
    • Aluminium clusters in the 21-55 atom range exhibit a variety of stable structures.
    • The study provides insights into the evolution of cluster geometry and the formation of icosahedral motifs.