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Abstract Photonic modes in dielectric nanostructures, e.g., wide gap semiconductor like CeO2 (ceria), have the potential for various applications such as information transmission and sensing technology. To fully understand the properties of such phenomenon at the nanoscale, electron energy-loss spectroscopy (EELS) in a scanning transmission electron microscope was employed to detect and explore photonic modes in well-defined ceria nanocubes. To facilitate the interpretation of the observations, EELS simulations were performed with finite-element methods. The simulations allow the electric and magnetic field distributions associated with different modes to be determined. A simple analytical eigenfunction model was also used to estimate the energy of the photonic modes. In addition, by comparing various spectra taken at different location relative to the cube, the effect of the surrounding environment on the modes could be sensed. This work gives a high-resolution description of the photonic modes' properties in nanostructures, while demonstrating the advantage of EELS in characterizing optical phenomena locally. 

Photon induced changes in charge distributions and conductivities of oxide nanoparticles (rhodium doped strontium titanate) have been determined using in situ electron holography. The holography-based approach relies on the application of two distinct stimuli to the material of interest: electrons and photons. The high energy electron beam stimulates the formation of a layer of positive surface charge due to secondary electron emission. Light illumination reduces this charge due to enhanced electronic conductivity arising from photo-electron excitation. For moderate photon and electron illumination rates, there is a simple linear relationship between the steady state surface charge and the sample conductivity. For rhodium doped strontium titanate, we observe a factor of 3 increase in the conductivity for the illumination conditions employed here. The approach is general and can be employed to measure photo-induced changes in other semiconducting systems. 

Materials functionalities may be associated with atomic-level structural dynamics occurring on the millisecond timescale. However, the capability of electron microscopy to image structures with high spatial resolution and millisecond temporal resolution is often limited by poor signal-to-noise ratios. With an unsupervised deep denoising framework, we observed metal nanoparticle surfaces (platinum nanoparticles on cerium oxide) in a gas environment with time resolutions down to 10 milliseconds at a moderate electron dose. On this timescale, many nanoparticle surfaces continuously transition between ordered and disordered configurations. Stress fields can penetrate below the surface, leading to defect formation and destabilization, thus making the nanoparticle fluxional. Combining this unsupervised denoiser with in situ electron microscopy greatly improves spatiotemporal characterization, opening a new window for the exploration of atomic-level structural dynamics in materials.