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Updated: Jan 25, 2026

Ligand Nano-cluster Arrays in a Supported Lipid Bilayer
Published on: April 23, 2017
GIGA: a versatile genetic algorithm for free and supported clusters and nanoparticles in the presence of ligands
Marc Jäger1, Rolf Schäfer, Roy L Johnston
1Technische Universität Darmstadt, Eduard-Zintl Institut für Anorganische und Physikalische Chemie, Alarich-Weiss-Straße 8, 64287 Darmstadt, Germany. jaeger@cluster.pc.chemie.tu-darmstadt.de.
Abstract:
We present a versatile parallelised genetic algorithm, which is able to perform global optimisation from first principles for pure and mixed free clusters in the gas phase, supported on surfaces or in the presence of one or several atomic or molecular species (ligands or adsorbates). The genetic algorithm is coupled to different quantum chemical software packages in order to permit a large variety of methods for the global optimisation. The genetic algorithm is also capable of optimising different electronic spin multiplicities explicitly, which allows global optimisation on several potential energy hypersurfaces in parallel. We employ the genetic algorithm to study ligand-passivated clusters [Cd3Se3(H2S)3]+ and to investigate adsorption of [Pt6(H2O)2]+ supported on graphene. The explicit consideration of the electronic spin multiplicity during global optimisation is investigated for nanoalloy clusters Pt4V2.
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