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arXiv · 1501.05855

Computational Design of Nanoclusters by Property-Based Genetic Algorithms: Tuning the Electronic Properties of (TiO$_2$)$_n$ Clusters

Saswata Bhattacharya·Benjamin H. Sonin·Christopher J. Jumonville·Luca M. Ghiringhelli·Noa Marom
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Abstract

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 (TiO$_2$)$_n$ 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 (TiO$_2$)$_n$ up to n=20 correlate more strongly with the presence of these structural features than with size.

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Saswata Bhattacharya, Benjamin H. Sonin, Christopher J. Jumonville, Luca M. Ghiringhelli, Noa Marom. 2015-01-23. Computational Design of Nanoclusters by Property-Based Genetic Algorithms: Tuning the Electronic Properties of (TiO$_2$)$_n$ Clusters. https://doi.org/10.1103/physrevb.91.241115

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