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

Bhattacharya S, Sonin BH, Jumonville CJ, Ghiringhelli LM, Marom N (2015)

Publication Type: Journal article

Publication year: 2015

Journal

Physical Review B - Condensed Matter and Materials Physics American Physical Society (APS)

Book Volume: 91

Article Number: 241115

Journal Issue: 24

DOI: 10.1103/PhysRevB.91.241115

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.

Authors with CRIS profile

Luca Ghiringhelli

Involved external institutions

Indian Institute of Technology (IIT), Delhi IN India (IN) Tulane University US United States (USA) (US) Fritz-Haber-Institut der Max-Planck-Gesellschaft (FHI) DE Germany (DE)

How to cite

APA:

Bhattacharya, S., Sonin, B.H., Jumonville, C.J., Ghiringhelli, L.M., & Marom, N. (2015). Computational design of nanoclusters by property-based genetic algorithms: Tuning the electronic properties of (TiO2)n clusters. Physical Review B - Condensed Matter and Materials Physics, 91(24). https://doi.org/10.1103/PhysRevB.91.241115

MLA:

Bhattacharya, Saswata, et al. "Computational design of nanoclusters by property-based genetic algorithms: Tuning the electronic properties of (TiO2)n clusters." Physical Review B - Condensed Matter and Materials Physics 91.24 (2015).

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