Liquid-phase transmission electron microscopy (LP-TEM) is a powerful characterization tool for probing the dynamics of nanometer-scale systems in a solvated environment. When the energetic electron beam (80–300 kV) interacts with the solvent, radiolysis occurs, generating highly reactive species that interact with the sample. While these species are often considered harmful and great efforts are taken to mitigate their influence, many of these radiolytic products, such as hydroxyl radicals and solvated electrons, are crucially relevant to several areas of energy research. In this Perspective, we propose a paradigm shift wherein solvent-derived, reactive radiolytic species generated by the electron beam are viewed as a tool for rational chemical perturbation of a material system rather than as a source of error to minimize. With an increased understanding of and control over the chemical kinetics governing the distribution of radiolytic species, LP-TEM is poised to allow for direct imaging of chemically driven, nanometer-scale dynamics, resulting in new insights into a range of energy-related materials.

Excitonics is a rapidly expanding field of nanophotonics in which the harvesting of photons, ensuing creation and transport of excitons via Förster resonant energy transfer (FRET), and subsequent charge separation or photon emission has led to the demonstration of excitonic wires, switches, Boolean logic and light harvesting antennas for many applications. FRET funnels excitons down an energy gradient resulting in energy loss with each step along the pathway. Conversely, excitonic energy upconversion via upconversion nanoparticles (UCNPs), although currently inefficient, serves as an energy ratchet to boost the exciton energy. Although FRET-based upconversion has been demonstrated, it suffers from low FRET efficiency and lacks the ability to modulate the FRET. We have engineered an upconversion FRET-based switch by combining lanthanide-doped UCNPs and fluorophores that demonstrates excitonic energy upconversion by nearly a factor of 2, an excited state donor to acceptor FRET efficiency of nearly 25%, and an acceptor fluorophore quantum efficiency that is close to unity. These findings offer a promising path for energy upconversion in nanophotonic applications including artificial light harvesting, excitonic circuits, photovoltaics, nanomedicine, and optoelectronics.

Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to reveal unexpected deformations that crucially affect material properties across a large sample area. Here, we demonstrate a rapid and semi-automated unsupervised machine learning approach to uncover lattice deformations in materials. Our method utilizes divisive hierarchical clustering to automatically unveil multi-scale deformations in the entire sample flake from the diffraction data using four-dimensional scanning transmission electron microscopy (4D-STEM). Our approach overcomes the current barriers of large 4D data analysis without a priori knowledge of the sample. Using this purely data-driven analysis, we have uncovered different types of material deformations, such as strain, lattice distortion, bending contour, etc., which can significantly impact the band structure and subsequent performance of nanomaterials-based devices. We envision that this data-driven procedure will provide insight into materials’ intrinsic structures and accelerate the discovery of materials.

Inorganic nanomaterials are often depicted as rigid structures whose shape is permanent. However, forces that are ordinarily considered weak can exert sufficient stress at the nanoscale to drive mechanical deformation. Here, we leverage van der Waals (VdW) interactions to mechanically reshape inorganic nanostructures from planar to curvilinear. Modified plate deformation theory shows that high-aspect-ratio two-dimensional particles can be plastically deformed via VdW forces. Informed by this finding, silver nanoplates were deformed over spherical iron oxide template particles, resulting in distinctive bend contour patterns in bright-field (BF) transmission electron microscopy (TEM) images. High-resolution TEM images of deformed areas reveal the presence of highly strained bonds in the material. Finally, we show that the distance between two nearby template particles allows for the engineering of several distinct curvilinear morphologies. This work challenges the traditional view of nanoparticles as static objects and introduces methods for postsynthetic mechanical shape control.

<p>Inorganic nanomaterials are often depicted as rigid structures whose shape is permanent. However, forces that are ordinarily considered weak can exert sufficient stress at the nanoscale to drive mechanical deformation. Here, we leverage van der Waals (VdW) interactions to mechanically reshape inorganic nanostructures from planar to curvilinear. Modified plate deformation theory shows that high aspect ratio 2D particles can be plastically deformed via VdW forces. Informed by this finding, silver nanoplates were deformed over spherical iron oxide template particles, resulting in distinctive bend contour patterns in bright field (BF) transmission electron microscopy (TEM) images. High resolution (HR) TEM images of deformed areas reveal the presence of highly strained bonds in the material. Finally, we show the distance between two nearby template particles allows for the engineering of several distinct curvilinear morphologies. This work challenges the traditional view of nanoparticles as static objects and introduces methods for post-synthetic mechanical shape control. </p>