Modeling the noble metal/TiO2 (110) interface with hybrid DFT functionals: a periodic electrostatic embedded cluster model study

The interaction of Au(n) and Pt(n) (n=2,3) clusters with the stoichiometric and partially reduced rutile TiO(2) (110) surfaces has been investigated using periodic slab and periodic electrostatic embedded cluster models. Compared to Au clusters, Pt clusters interact strongly with both stoichiometric...

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Bibliographic Details
Published in:The Journal of chemical physics 2010-10, Vol.133 (16), p.164703-164703
Main Authors: Ammal, Salai Cheettu, Heyden, Andreas
Format: Article
Language:English
Subjects:
ADSORPTION
CHEMICAL BONDS
CLUSTER MODEL
ELECTRONIC STRUCTURE
ELECTROSTATICS
Environmental Molecular Sciences Laboratory
FUNCTIONALS
NUCLEAR PHYSICS AND RADIATION PHYSICS
OXYGEN
RUTILE
SIMULATION
VACANCIES
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Summary:The interaction of Au(n) and Pt(n) (n=2,3) clusters with the stoichiometric and partially reduced rutile TiO(2) (110) surfaces has been investigated using periodic slab and periodic electrostatic embedded cluster models. Compared to Au clusters, Pt clusters interact strongly with both stoichiometric and reduced TiO(2) (110) surfaces and are able to enhance the reducibility of the TiO(2) (110) surface, i.e., reduce the oxygen vacancy formation energy. The focus of this study is the effect of Hartree-Fock exchange on the description of the strength of chemical bonds at the interface of Au/Pt clusters and the TiO(2) (110) surface. Hartree-Fock exchange helps describing the changes in the electronic structures due to metal cluster adsorption as well as their effect on the reducibility of the TiO(2) surface. Finally, the performance of periodic embedded cluster models has been assessed by calculating the Pt adsorption and oxygen vacancy formation energies. Cluster models, together with hybrid PBE0 functional, are able to efficiently compute reasonable electronic structures of the reduced TiO(2) surface and predict charge localization at surface oxygen vacancies, in agreement with the experimental data, that significantly affect computed adsorption and reaction energies.
ISSN:0021-9606
1089-7690
DOI:10.1063/1.3497037