Microscopy (Oxford, England)最新文献

The image contrast obtained in electron microscopy depends on the atomic number of the sample. Therefore, obtaining a clear contrast is challenging when samples composed of light elements (carbon materials and polymers) are embedded in the resin. Herein, a newly developed embedding composition exhibiting low viscosity and high electron density is reported, which can be solidified using physical or chemical methods. When used for carbon materials, this embedding composition allows clear microscopic observation with higher contrast compared to conventional resin embedding. Furthermore, details of the observation of samples such as graphite and carbon black using this embedding composition are reported.

Liquid-phase transmission electron microscopy (LPTEM) technique has been used to perform a wide range of in situ and operando studies. While most studies are based on the sample contrast change in the liquid, acquiring high qualitative results in the native liquid environment still poses a challenge. Herein, we present a novel and facile method to perform high-resolution and analytical electron microscopy studies in a liquid flow cell. This technique is based on removing the liquid from the observation area by a flow of gas. It is expected that the proposed approach can find broad applications in LPTEM studies.

Lipid droplets and membranes in radicle cells from desiccated embryonic axes of soybean (Glycine max) seeds were examined by a recently developed correlative light and electron microscopy system, which has been designed to facilitate the observation of identical locations using an upright reflected light microscope and compact SEM successively with minimum time lapse. Lipids are major components of membranes and are also stored in numerous lipid droplets lining plasma membranes in many seed cells. Fluorescently stained lipid droplets and membranes in the desiccated radicle cells were mainly located along the surface of shrunk protoplasm and around presumptive protein bodies, which will turn into vacuoles and increase their volume for radicle protrusion. Co-localization of lipid droplets and membranes suggests the presence of a membrane protection mechanism during desiccation and rehydration processes that ensures prompt elongation of radicle cells during germination.

To improve the performance of organic light-emitting diodes (OLEDs), it is essential to understand and control the electric potential in the organic semiconductor layers. Electron holography (EH) is a powerful technique for visualizing the potential distribution with a transmission electron microscope. However, it has a serious issue that high-energy electrons may damage the organic layers, meaning that a low-dose EH is required. Here, we used a machine learning technique, three-dimensional (3D) tensor decomposition, to denoise electron interference patterns (holograms) of bilayer OLEDs composed of N,N'-di-[(1-naphthyl)-N,N'-diphenyl]-(1,1'-biphenyl)-4,4'-diamine (α-NPD) and tris-(8-hydroxyquinoline)aluminum (Alq3), acquired under a low-dose rate of 130 e- nm-2 s-1. The effect of denoising on the phase images reconstructed from the holograms was evaluated in terms of both the phase measurement error and the peak signal-to-noise ratio. We achieved a precision equivalent to that of a conventional measurement that had an exposure time 60 times longer. The electric field within the Alq3 layer decreased as the cumulative dose increased, which indicates that the Alq3 layer was degraded by the electron irradiation. On the basis of the degradation of the electric field, we concluded that the tolerance dose without damaging the OLED sample is about 1.7 × 105 e- nm-2, which is about 0.6 times that of the conventional EH. The combination of EH and 3D tensor decomposition denoising is capable of making a time series measurement of an OLED sample without any effect from the electron irradiation.

Electrically assisted heat treatment is the process of applying an electric current to a sample during heat treatment. Literature has generally shown there to be a difference in the resulting effects of direct current (DC) current and highly transient current (i.e. electropulsing). However, these differences are poorly characterized. In situ transmission electron microscopy (TEM) observation of an AA7075 sample while DC and pulsed current were passed through it was performed herein to explore the effects of an electric current on precipitate development. Numerical simulation results indicate that the thermal response of the samples was very rapid, causing the sample to reach steady-state temperatures almost instantly. There does not appear to be any significant difference between the results of pulsed current application and DC current. Additionally, the failure mechanism of an electrical biasing TEM sample is explored.

Pairs of silicon carbide nanowires were grown side by side synchronously from the same metal catalyst nanoparticles. The stacking sequences of each pair were read by high-resolution transmission electron microscopy, and the similarity of each stacking sequence was measured using the Levenshtein distance. No synchronism was detected in the pairs of stacking sequences, and the results indicated that the formation of stacking faults in silicon carbide nanowires was not deterministic, but purely stochastic.

We have developed a method to quantitatively measure image distortion, one of the five Seidel aberrations, in transmission electron microscopes without using a standard sample with a known structure. Displacements of small local segments in an image due to image distortion of the intermediate and projection lens system are first measured by comparing images taken before and after a given shift at the first image plane of the objective lens. Then, the sum of the second partial derivatives, or the Laplacian, of the displacement field is measured, and the radial and azimuthal distortion parameters are determined from the measured results. We confirmed using numerically distorted images that the proposed method can measure the image distortion within a relative error ratio of 0.04 for a wide range of distortion amount from 0.1% to 5.0%. The distortion measurement and correction were confirmed to work correctly by using the experimental images, and the iterative measurement and correction procedure could reduce the distortion to a level where the average image displacement was < 0.05 pixels.

Diffraction patterns contain useful information about the materials. Recent developments in four-dimensional scanning transmission electron microscopy and the acquisition of the spatial distribution of diffraction patterns have produced significant results. The acquisition of a temporal series of diffractions is achieved for a stationary beam. However, the acquisition of spatiotemporal distribution of diffraction patterns has only been established under limited conditions. In this study, we developed a simple method that enables the recording of the spatiotemporal distribution of diffraction patterns and applied it to the relaxation time measurement that is robust to sample drift.

Scanning electron microscopy (SEM) has realized high-throughput defect monitoring of semiconductor devices. As miniaturization and complexification of semiconductor circuit patterns increase in recent years, so has the number of defects. There is thus a great need to further increase the throughput of SEM defect monitoring. Toward this end, we propose a deep learning-based super-resolution method that reproduces high-resolution (HR) images from corresponding low-resolution images. Image quality factors such as pattern contrast and sharpness are important in SEM HR images in order to evaluate the quality of printed circuit patterns. Our proposed method meets various image quality requirements by changing the loss calculation method pixelwise based on the pattern in the image. It realizes super-resolved images that compare favorably with actual HR images and can improve SEM throughput by 100% or more.