Microscopy (Oxford, England)最新文献

Spectral image (SI) measurement techniques, such as X-ray absorption fine structure (XAFS) imaging and scanning transmission electron microscopy (STEM) with energy-dispersive X-ray spectroscopy (EDS) or electron energy loss spectroscopy (EELS), are useful for identifying chemical structures in composite materials. Machine-learning techniques have been developed for automatic analysis of SI data and their usefulness has been proven. Recently, an extended measurement technique combining SI with a computed tomography (CT) technique (CT-SI), such as CT-XAFS and STEM-EDS/EELS tomography, was developed to identify the three-dimensional (3D) structures of chemical components. CT-SI analysis can be conducted by combining CT reconstruction algorithms and chemical component analysis based on machine-learning techniques. However, this analysis incurs high-computational costs owing to the size of the CT-SI datasets. To address this problem, this study proposed a fast computational approach for 3D chemical component analysis in an unsupervised learning setting. The primary idea for reducing the computational cost involved compressing the CT-SI data prior to CT computation and performing 3D reconstruction and chemical component analysis on the compressed data. The proposed approach significantly reduced the computational cost without losing information about the 3D structure and chemical components. We experimentally evaluated the proposed approach using synthetic and real CT-XAFS data, which demonstrated that our approach achieved a significantly faster computational speed than the conventional approach while maintaining analysis performance. As the proposed procedure can be implemented with any CT algorithm, it is expected to accelerate 3D analyses with sparse regularized CT algorithms in noisy and sparse CT-SI datasets.

We have demonstrated a quantification of all component wires in a bent electric cable, which is necessary for discussion of cable products in actual use cases. Quantification became possible for the first time because of our new technologies for image analysis of bent cables. In this paper, various image analysis techniques to detect all wire tracks in a bent cable are demonstrated. Unique cross-sectional image construction and deep active learning schemes are the most important items in this study. These methods allow us to know the actual state of cables under external loads, which makes it possible to elucidate the mechanisms of various phenomena related to cables in the field and further improve the quality of cable products.

This study proposes a simple evaluation method for deriving L-absorption information from two L-emission spectra of 3d transition metal (TM) elements obtained at two different accelerating voltages. This method realizes a spatial identity for X-ray emission and absorption spectroscopies. This method was evaluated for the Fe L-emission spectra of Fe and its oxides and was applied to the TM L-emission spectra of MnO, Co, CoO and NiO. The derived absorption peak positions were consistent with those obtained previously at synchrotron orbital radiation facilities, which considered the core-hole effect. This simple derivation method could be useful for obtaining X-ray absorption spectroscopy distribution images from X-ray emission spectroscopy mapping data obtained by scanning electron microscopy.

Adapting to environmental changes and formulating behavioral strategies are central to the nervous system, with the prefrontal cortex being crucial. Chronic stress impacts this region, leading to disorders including major depression. This review discusses the roles for prefrontal cortex and the effects of stress, highlighting similarities and differences between human/primates and rodent brains. Notably, the rodent medial prefrontal cortex is analogous to the human subgenual anterior cingulate cortex in terms of emotional regulation, sharing similarities in cytoarchitecture and circuitry, while also performing cognitive functions similar to the human dorsolateral prefrontal cortex. It has been shown that chronic stress induces atrophic changes in the rodent mPFC, which mirrors the atrophy observed in the subgenual anterior cingulate cortex and dorsolateral prefrontal cortex of depression patients. However, the precise alterations in neural circuitry due to chronic stress are yet to be fully unraveled. The use of advanced imaging techniques, particularly volume electron microscopy, is emphasized as critical for the detailed examination of synaptic changes, providing a deeper understanding of stress and depression at the molecular, cellular and circuit levels. This approach offers invaluable insights into the alterations in neuronal circuits within the medial prefrontal cortex caused by chronic stress, significantly enriching our understanding of stress and depression pathologies.

The detective quantum efficiency (DQE) is generally accepted as the main figure of merit for the comparison between electron detectors, and most of the time given as a unique number at the Nyquist frequency while it is known to vary with electron dose. It is usually estimated, thanks to a method improved by McMullan in 2009. The purpose of this work is to analyze and to criticize this DQE extraction method on the basis of measurement and model results, and to give recommendations for fair comparison between detectors, wondering if the DQE is the right figure of merit for electron detectors.

We report a novel class of scanning transmission electron microscopy with Hilbert-differential phase contrast (HDP-STEM) that displays nanostructures of thin samples in a topographical manner. A semicircular π-phase plate (PP) was used as an optical device for manipulating electron waves in HDP-STEM. This is the different design from the Zernike PP used in our previous phase plate STEM (P-STEM), but both must be placed in the front focal plane of the condenser lens. HDP-STEM images of multiwalled carbon nanotubes showed higher contrast than those obtained by conventional bright-field STEM. As the PP of the HDP-STEM is nonsymmetrical, several different images were obtained by changing the detection conditions. A two-dimensional electron detector was also used to remove the scattering contrast component in the same way as with the Zernike PP and obtain an image containing only (differential) phase contrast.

Correlative array tomography, combining light and electron microscopy via serial sections, plays a crucial role in the three-dimensional ultrastructural visualization and molecular distribution analysis in biological structures. To address the challenges of aligning fluorescence and electron microscopy images and aligning serial sections of irregularly shaped biological specimens, we developed a diamond notch knife, a new tool for puncturing holes using a diamond needle. The diamond needle featured a triangular and right-angled tip, enabling the drilling of deep holes upon insertion into the polished block face. This study describes the application of the diamond notch knife in correlative array tomography.

We report direct observation by electron holography of the spin polarization of electrons in a vacuum region around a charged SiO2 wire coated with Pt-Pd. Irradiating the SiO2 wire with 300 keV electrons caused the wire to become positively charged due to the emission of secondary electrons. The spin polarization of these electrons interacting with the charged wire was observed in situ using a phase reconstruction process under an external magnetic field. The magnetic field of the spin-polarized electrons was simulated taking into account the distribution of secondary electrons and the effect of the external magnetic field.

The polymer electrolyte fuel cell (PEFC) is one of the strongest candidates for a next-generation power source for vehicles which do not emit CO2 gas as exhaust gas. The key factor in PEFCs is the nano-scaled electrochemical reactions that take place on the catalyst material and an ionomer supported by a carbon support. However, because the nano-scaled morphological features of the key materials in the catalyst compound cannot be observed clearly by transmission electron microscopy, improvement of PEFC performance had been approached by an imaginal schematic diagram based on an electrochemical analysis. In this study, we revealed the nano-scaled morphological features of the PEFC electrode in three dimensions and performed a quantitative analysis of the nanostructure by the newly developed 'Combined ADF-STEM tomography technique'. This method combines information from plural annular darkfield detectors with different electron collection angles and can emphasize the difference of the electron scattering intensity between the ionomer and carbon in the cross-sectional image of the reconstructed three-dimensional (3D) data. Therefore, this segmentation method utilizing image contrast does not require a high electron beam current like that used in energy dispersive X-ray analysis, and thus is suitable for electron beam damage-sensitive materials. By eliminating the process of manually determining the thresholds for obtaining classified component data from grayscale data, the obtained 3D structures have sufficient accuracy to allow quantitative analysis and specify the nano-scaled structural parameters directly related to power generation characteristics.