High-power laser irradiation for high-temperature in situ transmission electron microscopy

Focused light introduction into transmission electron microscope via parabolic mirror

We developed a novel light optics system installed in a scanning transmission electron microscope (STEM) to introduce a focused light accurately adjusted at the electron beam irradiation position using a parabolic mirror. With a parabolic mirror covering both the upper and lower sides of the sample, the position and focus of the light beam can be evaluated by imaging the angular distribution of the transmitted light. By comparing the light image and the electron micrograph, the irradiation positions of the electron beam and the laser beam can be accurately adjusted to each other. The size of the focused light was confirmed to be within a few microns from the light Ronchigram, which is consistent with the simulated light spot size. The spot size and position alignment were further confirmed by laser-ablating only a targeted polystyrene particle without damaging the surrounding particles. When using a halogen lamp as the light source, this system allows investigating optical spectra in comparison with cathodoluminescence (CL) spectra at exactly the same location.

A Review on Recent Progress in Preparation of Medium-Temperature Solar-Thermal Nanofluids with Stable Dispersion

Direct absorption of sunlight and conversion into heat by uniformly dispersed photothermal nanofluids has emerged as a facile way to efficiently harness abundant renewable solar-thermal energy for a variety of heating-related applications. As the key component of the direct absorption solar collectors, solar-thermal nanofluids, however, generally suffer from poor dispersion and tend to aggregate, and the aggregation and precipitation tendency becomes even stronger at elevated temperatures. In this review, we overview recent research efforts and progresses in preparing solar-thermal nanofluids that can be stably and homogeneously dispersed under medium temperatures. We provide detailed description on the dispersion challenges and the governing dispersion mechanisms, and introduce representative dispersion strategies that are applicable to ethylene glycol, oil, ionic liquid, and molten salt-based medium-temperature solar-thermal nanofluids. The applicability and advantages of four categories of stabilization strategies including hydrogen bonding, electrostatic stabilization, steric stabilization, and self-dispersion stabilization in improving the dispersion stability of different type of thermal storage fluids are discussed. Among them, recently emerged self-dispersible nanofluids hold the potential for practical medium-temperature direct absorption solar-thermal energy harvesting. In the end, the exciting research opportunities, on-going research need and possible future research directions are also discussed. It is anticipated that the overview of recent progress in improving dispersion stability of medium-temperature solar-thermal nanofluids can not only stimulate exploration of direct absorption solar-thermal energy harvesting applications, but also provide a promising means to solve the fundamental limiting issue for general nanofluid technologies.

FFT pattern recognition of crystal HRTEM image with deep learning

Rapid analysis and processing of large quantities of data obtained from in-situ transmission electron microscope (TEM) experiments can save researchers from the burdensome manual analysis work. The method mentioned in this paper combines deep learning and computer vision technology to realize the rapid automatic processing of end-to-end crystal high-resolution transmission electron microscope (HRTEM) images, which has great potential in assisting TEM image analysis. For the fine-grained result, the HRTEM image is divided into multiple patches by sliding window, and 2D fast Fourier transform (FFT) is performed, and then all FFT images are inputted into the designed LCA-Unet to extract bright spots. LCA-Unet combines local contrast and attention mechanism on the basis of U-net. Even if the bright spots in FFT images are weak, the proposed neural network can extract bright spots effectively. Using computer vision and the information of bright spots above mentioned, the automatic FFT pattern recognition is completed by three steps. First step is to calculate the precise coordinates of the bright spots, the lattice spacings and the inter-plane angles in each patch. Second step is to match the lattice spacing and the angles with the powder diffraction file (PDF) to determine the material phase of each patch. Third step is to merge the patches with same phase. Taking the HRTEM image of zirconium and its oxide nanoparticles as an example, the results obtained by the proposed method are basically consistent with manual identification. Thus the approach could be used to automatically and effectively find the phase region of interest. It takes about 3 s to process a 4 K × 4 K HRTEM image on a modern desktop computer with NVIDIA GPU.

Solid state molybdenum carbide nanomotors driven via high temperature carbon-decomposition catalytic reactions

The motion of solid state nanomotors, i.e., molybdenum carbide nanoparticles, which were driven via carbon-decomposition catalytic reactions at ∼2900 K, was directly observed by in situ transmission electron microscopy. The nanomotors exhibited unidirectional linear motions inside the hollow space of multiwall carbon nanotubes, reciprocating motions around the nanotube endcaps, and rotational motions in the hollow spaces of carbon nanocapsules. The inner atomic wall-layers of carbon nanotubes and nanocapsules were consumed during the nanomotor motions.

Time series of TEM images observed in the motion of a MoC nanomotor encapsulated in a carbon nanotube during in situ laser irradiation.