Microscopy (Oxford, England)最新文献

Improvement of a commercially available soft X-ray emission spectrometer was tested by introducing a fine-pixel-sized CMOS detector. The peak width of Mg Kα-emission was reduced to one-fourth of that obtained by the CCD detector presently used. Furthermore, the differences in the energy positions of satellite lines of Mg Kα- and also Kβ-emission profiles of Mg and MgO were observed. O K-emission profile of MgO exhibited a few structures reflecting the chemical bonding state. This spectrometer easily discriminated the intensity profiles of Fe Lα,β-emission reflecting the chemical bonding states of Fe atoms in Fe, FeO, Fe3O4 and Fe2O3.

According to theoretical predictions, local strain in the bent regions of flexible nanowires can alter their electronic structure. However, the experimental validation of such strain-induced effects remains elusive. In this study, we established a clear correlation between local structural deformation and electronic properties in bent hexagonal-WO3 nanowires using four-dimensional scanning transmission electron microscopy and electron energy loss spectroscopy. Although a simple geometric bending model predicts an expansion of the (0001) lattice spacing on the outer side of the bend, our direct observations revealed a larger expansion than predicted. This lattice expansion was accompanied by a significant reduction in bandgap energy. We employed density functional theory calculations and crystal orbital Hamilton population analyses to provide a theoretical framework for these findings. These results provide direct experimental evidence of strain-induced modulation of the electronic structure in metal oxide nanowires.

Electron spectroscopy implemented in electron microscopes provides high spatial resolution, down to the atomic scale, of the chemical, electronic, vibrational and optical properties of materials. In this review, we will describe how temporal coincidence experiments in the nanosecond to femtosecond range between different electron spectroscopies involving photons, inelastic electrons and secondary electrons can provide information bits not accessible to independent spectroscopies. In particular, we will focus on nano-optics applications. The instrumental modifications necessary for these experiments are discussed, as well as the perspectives for these coincidence techniques.

Knife-mark noise often arises in microscopy of materials. Leveraging their simple textures relative to natural images, we simulate knife-marked micrographs and train a deep network without labeled real data. The resulting model surpasses conventional methods, removing artifacts while preserving structure, demonstrating simulation-driven learning as a practical materials-science solution in research. Accurate quantitative analysis of material microstructures from images is often hindered by noise and artifacts generated during sample preparation. While deep learning is a promising approach for this challenge, preparing the large amount of "supervised data" (labeled real images) required for training poses a significant barrier in material science. This study proposes and validates a simulation-driven learning paradigm where a deep learning model is trained exclusively on simulated images that mimic the key features of target structures and noise, serving as a powerful solution to this data scarcity problem. As a specific case study, we applied this paradigm to the removal of "knife-mark noise" from cross-sectional images of rubber materials to enable accurate filler region segmentation. In evaluations using simulated data, the proposed method showed superior performance across all the metrics (PSNR, SSIM, and MAE) compared with conventional methods such as the median filter and TV reconstruction, as well as a U-Net model trained on general-purpose Gaussian noise. More importantly, the model also performed effectively on real images, despite being trained solely on simulated data. It successfully removed both knife-marks and material-derived background textures, which demonstrates the viability of simulation-driven learning to overcome the need for manually annotated datasets. This work highlights the power of task-specific simulations as a practical alternative to manual data annotation in quantitative materials analysis.

Dynamics in liquids and glasses can be assessed using X-ray photon correlation spectroscopy or electron correlation microscopy, which involves measuring the temporal changes in diffraction patterns. Two methods are commonly used to evaluate these temporal changes: one-time correlation function or two-time correlation function. However, the specific characteristics of these methods have not been thoroughly studied. In this study, we investigated the differences between these methods and found that the two-time correlation function can measure dynamics for longer periods than the method relying on the one-time correlation function. Additionally, we demonstrated that the two-time correlation function exhibits a weak dependence on the amount of dose applied.

Atomic force microscopy (AFM) has developed remarkably in recent years, and its measurement environment has been extended not only to ultrahigh vacuum and air, but also to liquids. Since the solid-liquid interface is the site of various reactions, such as crystal growth and catalytic reactions, its atomic-scale analysis is crucially important. Although AFM analyses in various liquids, such as aqueous solutions, organic solvents, and ionic liquids, have been reported, there have been no studies of AFM analysis in molten metals. One of the reasons for this is the opacity of molten metals. Achieving AFM analysis in molten metal is expected to provide new insights into metallurgy. In this review, AFM that can analyze in molten metal is presented. The key innovation is the utilization of an AFM sensor employing a quartz tuning fork, the so-called qPlus sensor, instead of a silicon cantilever. In addition to the technical fundamentals of AFM in molten metal, we present two applications: in-situ and atomic-resolution analysis of alloy crystal growth processes and measurements of two-body interaction forces.

Bone dynamically changes its shape and structure in response to extra-tissue environments, so that bone morphometry has been a substantial method to evaluate pathophysiology of bone. Osteocytes embedded in mineralized bone matrix play key roles in systemic bone metabolism and characterize distinct bone sites. The jawbone has been described as a unique bone in the context of vertebrate evolution and function. Bone loss in the mandibular bone is less obvious in osteoporotic conditions than in other bones, such as vertebral and limb long bones, both in animal models and in clinical studies. Since osteocyte lacunae are complex and small (-10µm in length) in shape and size, respectively, comprehensive and unbiased morphometrical analysis of changes in the size of osteocyte lacunae was still an obstacle. This study established an artificial intelligence-driven morphometry with wide-field microscopy-based imaging of osteocyte lacunae. Successive comparative analyses demonstrated active perilacunar bone remodeling in the mandibular bone than in the parietal bone. This approach enabled us to statistically compare morphometric parameters in a more comprehensive and unbiased manner. We further discuss the possible unique contribution of the mandibular bone to the pathophysiology of osteoporosis. This study established an artificial intelligence-driven morphometry with wide-field microscopy-based imaging of osteocyte lacunae. Successive comparative analyses demonstrated active perilacunar bone remodeling in the mandibular bone than in the parietal bone. This approach enabled us to statistically compare morphometric parameters in a more comprehensive and unbiased manner.

Cryoelectron microscopy is a powerful technique for high-resolution imaging of nonaqueous liquids, but challenges remain regarding imaging and data interpretation. Recent advancements in estimating the physicochemical properties of pure organic liquids at cryogenic temperatures have enhanced the selection of imaging and pre-treatment conditions. However, whether binary mixtures behave similarly to pure substances is still unclear. Furthermore, focused ion beam (FIB) milling facilitates site-specific cross-sectioning, but its effects on the microscopic morphology of frozen organic liquids are not well understood. In this study, we investigated water-tetrahydrofuran (THF) binary mixtures as a model to explore their phase behavior and radiation damage under cryogenic conditions. Spectroscopic analyses indicated microscopic phase separation within the seemingly miscible water-THF mixtures, but their detailed structure has been a subject of ongoing debate. Using cryo-scanning electron microscopy with FIB (cryo-FIB-SEM), we visualized bicontinuous phase-separation. The domain sizes were consistent across spectroscopic data, thermally sublimed surfaces, and FIB cross-sections. Notably, FIB milling caused a significant loss of THF-rich regions, likely due to localized temperature increases of approximately 178 K, which is an order of magnitude greater than that in water-rich domains. We also noted the nanoparticles of electron-resistant carbazole-terminated carbon-bridged oligo(para-phenylenevinylene) (COPV2-G1) formed within the THF-rich phase. Extended electron irradiation led to morphological changes and shrinkage, suggesting THF was incorporated into COPV2-G1 aggregates along with THF decomposition induced by the electron beam. These findings underscore critical considerations in cryo-FIB-SEM imaging of binary organic liquids and solvated particles, providing practical insights for reducing or leveraging ion/electron beam-induced artifacts.

Isotope microscopic imaging and atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-MALDI-MSI) provide powerful, complementary approaches for visualizing metabolic dynamics in biological tissues. This study applied these techniques to termite workers fed with 13C-labeled cellulose for one week. Termites are classified as eusocial insects because of their colonies' clear division of labor. The two primary castes in their life cycle are reproductive (king and queen), responsible for reproduction, and non-reproductive (workers and soldiers), who handle tasks such as defense, brood care, and foraging. Although various techniques have been developed to detect 13C-labeled biomolecules in samples, it remains unclear whether the iMScopeTM prototype can visualize these molecules with high spatial resolution. Advanced isotope microscopic imaging technique with high spatial resolution (200-300 nm) offered ultra-high-resolution visualization of the relative abundance of the 13C/12C distribution, suggesting precise localization of isotope enrichment in the abdomen. AP-MALDI-MSI performed in the iMScopeTM prototype enabled spatial mapping of 13C-labeled and unlabeled metabolites, such as acetyl-L-carnitine (ALC) and phosphatidylethanolamine (PE), by detecting characteristic mass shifts due to 13C incorporation. The accumulation of PE in the termite abdomen represents an adaptive strategy to optimize nutrient allocation and promote social cohesion, thereby highlighting its potential role in maintaining colony fitness. Our study shows that the iMScopeTM prototype is a novel AP-MALDI-MSI technique to detect 13C-integrated metabolites in the 13C-labeled sample. This study also demonstrated that this technique can detect 13C-integrated PE, which is abundant mainly in termite abdomen.

This review examines the effects of thermal vibrations on core-level excitation spectra, with a particular emphasis on the Ti L  2,3-edge spectra of cubic perovskite-type titanium oxides (SrTiO3 and PbTiO3). Based on combining scanning transmission electron microscopy energy-loss near-edge structure analyses with cluster-type crystal-field multiplet calculations, the influence of atomic thermal vibrations on the fine structure of the Ti L  2,3-edge is investigated, and it is demonstrated that the thermal vibration of oxygen atoms in cubic SrTiO3 can be estimated from the spectrum by fitting experimental and theoretical results. The same approach was extended to cubic PbTiO3 such that isotropic thermal vibrations were identified that relate to the difference in the transition to a low-temperature tetragonal phase. Although the present technique does not directly resolve phonon modes, it treats thermal factors as adjustable parameters, enabling the identification of subtle vibrational features even in materials already widely studied. Further investigation of the relationship between thermal vibrations and the fine structure of core-loss spectra could assist in elucidating certain material properties. This review explores the effects of thermal vibrations on Ti L  2,3-edge spectra of cubic perovskite oxides (SrTiO3, PbTiO3). Combining STEM-ELNES with crystal-field multiplet calculations, it shows that oxygen thermal vibrations can be estimated from spectral fitting, revealing subtle vibrational features and their relation to phase transitions.