Capturing experimental properties in computationally efficient faceted titania nanoparticle models

Understanding the surface chemistry of nanostructured TiO2 has long been a priority to improve photochemical device efficiency. Faceted nanoparticles, characterized by known facets not at thermodynamically ideal ratios, are particularly challenging to model due to the large number of chemical and computational parameters that must be chosen for which there is no experimental guidance. This research supplies a modeling framework for faceted TiO2 nanoparticles that provides rationale for such decisions. By performing full DFT optimization and characterization on a series of inter-related anatase TiO2 nanoparticles displaying {101}, (001), and {010} facets with sizes up to 202 TiO2 units, parameter space is mapped with regard to particle size, shape, defects, and optimization protocol. Specifically, it is shown that pre-optimization is necessary in order to achieve a sufficiently delocalized electronic structure, and the increased reorganization afforded by removing higher coordinated Ti atoms compensates the high formation energy of creating these defects. Furthermore, by characterizing differently shaped nanoparticles with the same number of TiO2 units, this research provides direct observation of shape effects on nanoparticles.