Atomic Scale Characterization of Fluxional Cation Behavior on Nanoparticle Surfaces: Probing Oxygen Vacancy Creation/Annihilation at Surface Sites.

Oxygen vacancy creation and annihilation are key processes in nonstoichiometric oxides such as CeO. The oxygen vacancy creation and annihilation rates on an oxide's surface partly govern its ability to exchange oxygen with the ambient environment, which is critical for a number of applications including energy technologies, environmental pollutant remediation, and chemical synthesis. Experimental methods to probe and correlate local oxygen vacancy reaction rates with atomic-level structural heterogeneities would provide significant information for the rational design and control of surface functionality; however, such methods have been unavailable to date.

Tracking the picoscale spatial motion of atomic columns during dynamic structural change.

In many materials systems, such as catalytic nanoparticles, the ability to characterize dynamic atomic structural changes is important for developing a more fundamental understanding of functionality. Recent developments in direct electron detection now allow image series to be acquired at frame rates on the order of 1000 frames per second in bright-field transmission electron microscopy (BF TEM), which could potentially allow dynamic changes in the atomic structure of individual nanoparticles to be characterized with millisecond temporal resolution in favorable cases. However, extracting such data from TEM image series requires the development of computational methods that can be applied to very large datasets and are robust in the presence of noise and in the non-ideal imaging conditions of some types of environmental TEM experiments.

Approaches to Exploring Spatio-Temporal Surface Dynamics in Nanoparticles with Transmission Electron Microscopy.

Many nanoparticles in fields such as heterogeneous catalysis undergo surface structural fluctuations during chemical reactions, which may control functionality. These dynamic structural changes may be ideally investigated with time-resolved in situ electron microscopy. We have explored approaches for extracting quantitative information from large time-resolved image data sets with a low signal to noise recorded with a direct electron detector on an aberration-corrected transmission electron microscope.