Abstract

Accurate statistical characterization of nanomaterials is crucial for their use in emerging technologies. This work investigates how different structural characteristics of metal nanoparticles influence the line profiles of the corresponding powder diffraction pattern. The effects of crystallite size, shape, lattice dynamics, and faulting are all systematically studied in terms of their impact on the line profiles. The studied patterns are simulated from atomistic models of nanoparticles via the Debye function. This approach allows for the existing theories of diffraction to be tested, and extended, in an effort to improve the characterization of small crystallites. It also begins to allow for the incorporation of atomistic simulations into the field of diffraction. Molecular dynamics simulations are shown to be effective in generating realistic structural models and dynamics of an atomic system, and are then used to study the observed features in the powder diffraction pattern. Furthermore, the characterization of a sample of shape controlled Pt nanoparticles is carried out through the use of a developed Debye function analysis routine in an effort to determine the predominant particle shape. The results of this modeling are shown to be in good agreement with complementary characterization methods, like transmission electron microscopy and cyclic voltammetry.