Premium
Geometry Optimisation of Aluminium Clusters Using a Genetic Algorithm
Author(s) -
Lloyd Lesley D.,
Johnston Roy L.,
Roberts Christopher,
MortimerJones Thomas V.
Publication year - 2002
Publication title -
chemphyschem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 140
eISSN - 1439-7641
pISSN - 1439-4235
DOI - 10.1002/1439-7641(20020517)3:5<408::aid-cphc408>3.0.co;2-g
Subject(s) - icosahedral symmetry , aluminium , hexagonal crystal system , crystallography , materials science , geometry , algorithm , chemistry , computer science , mathematics , metallurgy
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 Al 55 having a centred icosahedral structure. Evolutionary Progress Plots for Al 19 and Al 38 reveal how the best structure evolves from generation to generation upon operation of the Genetic Algorithm.