Capturing experimental properties in computationally efficient faceted
titania nanoparticle models
Abstract
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.