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

Saswata Bhattacharya, Benjamin H. Sonin, Christopher J. Jumonville, Luca M. Ghiringhelli, and Noa Marom
Phys. Rev. B 91, 241115(R) – Published 26 June 2015
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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 (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.

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  • Received 19 January 2015

DOI:https://doi.org/10.1103/PhysRevB.91.241115

©2015 American Physical Society

Authors & Affiliations

Saswata Bhattacharya1, Benjamin H. Sonin2, Christopher J. Jumonville2, Luca M. Ghiringhelli3,*, and Noa Marom2,*

  • 1Department of Physics, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016, India
  • 2Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, USA
  • 3Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany

  • *Corresponding authors: ghiringhelli@fhi-berlin.mpg.de; nmarom@tulane.edu

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Issue

Vol. 91, Iss. 24 — 15 June 2015

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