title: Geometry optimisation of aluminium clusters using a genetic algorithm.
abstract: The application of a Genetic Algorithm, for optimising the geometry of aluminium clusters with 21-55 atoms bound by the many-body Murrell-Mottram potential, is described. In this size regime, a number of different structural motifs are identified--face-centred cubic, hexagonal close packed, decahedral and icosahedral structures. The larger clusters consist of hollow icosahedral geometric shells, with Al55 having a centred icosahedral structure. Evolutionary Progress Plots for Al19 and Al38 reveal how the best structure evolves from generation to generation upon operation of the Genetic Algorithm.
authors.affiliation: School of Chemical Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
authors.forename: Lesley D
authors.initials: LD
authors.lastname: Lloyd
authors.forename: Roy L
authors.initials: RL
authors.lastname: Johnston
authors.forename: Christopher
authors.initials: C
authors.lastname: Roberts
authors.forename: Thomas V
authors.initials: TV
authors.lastname: Mortimer-Jones