Computational design of nanoclusters by property-based genetic algorithms: Tuning the electronic properties of (TiO2)n clusters

In order to design clusters with desired properties, we have implemented a suite of genetic algorithms tailored to optimize for low total energy, high vertical electron affinity (VEA), and low vertical ionization potential (VIP). Applied to (TiO2)(n) clusters, the property-based optimization reveals the underlying structure-property relations and the structural features that may serve as active sites for catalysis. High VEA and low VIP are correlated with the presence of several dangling-O atoms and their proximity, respectively. We show that the electronic properties of (TiO2)(n) up to n = 20 correlate more strongly with the presence of these structural features than with size.