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Reliable and computationally affordable prediction of the energy gap of (TiO2)(n) (10 <= n <= 563) nanoparticles from density functional theory

Research areaChemistry and Materials Science and Technology
TitleReliable and computationally affordable prediction of the energy gap of (TiO2)(n) (10 <= n <= 563) nanoparticles from density functional theory
Publication TypeJournal Article
Publication year2018
AuthorsMorales-García, Á, Valero, R, Illas, F
JournalPhysical Chemistry Chemical Physics
Volume20
Number28
Pages18907–18911
DOI10.1039/c8cp03582b