title: A genetic algorithm for first principles global structure optimization of supported nano structures.
abstract: We present a newly developed publicly available genetic algorithm (GA) for global structure optimisation within atomic scale modeling. The GA is focused on optimizations using first principles calculations, but it works equally well with empirical potentials. The implementation is described and benchmarked through a detailed statistical analysis employing averages across many independent runs of the GA. This analysis focuses on the practical use of GA's with a description of optimal parameters to use. New results for the adsorption of M8 clusters (M = Ru, Rh, Pd, Ag, Pt, Au) on the stoichiometric rutile TiO2(110) surface are presented showing the power of automated structure prediction and highlighting the diversity of metal cluster geometries at the atomic scale.
authors.affiliation: Interdisciplinary Nanoscience Center (iNANO) and Department of Physics and Astronomy, Aarhus University, DK-8000 Aarhus C, Denmark.
authors.forename: Lasse B
authors.initials: LB
authors.lastname: Vilhelmsen
authors.affiliation: Interdisciplinary Nanoscience Center (iNANO) and Department of Physics and Astronomy, Aarhus University, DK-8000 Aarhus C, Denmark.
authors.forename: Bjørk
authors.initials: B
authors.lastname: Hammer
mesh_terms: D000327:Adsorption; D000465:Algorithms; D019216:Metals, Heavy / Q000737:chemistry; D008956:Models, Chemical; D008957:Models, Genetic; D049329:Nanostructures / Q000737:chemistry*; D013499:Surface Properties; D014025:Titanium / Q000737:chemistry
chemical_list: D019216:Metals, Heavy; C009495:titanium dioxide; D014025:Titanium