Microscopy (Oxford, England)最新文献

Electron microscopy using an environmental cell is a powerful tool for observing catalysts and other nanomaterials in gases and liquids. An environmental cell must contain amorphous silicon-nitride membranes because they protect the sample environment from the vacuum of the electron microscope and enable the electron beam to pass through the cell. However, the membranes superimpose non-uniform contrast on the projected image, degrading image quality. We propose a method for removing the noise derived from the membranes using Noise2Noise, a deep-learning method, for a series of transmission-electron-microscope images with slight electron-beam tilt and evaluated its effectiveness. We succeeded in removing the membrane-derived noise while retaining the information of the sample in the cell. We also succeeded in efficiently removing Poisson noise. We believe this method will enable measurements requiring high signal-to-noise ratios, which could previously only be observed in a vacuum, to be conducted in an environmental cell.

Organosilica nanoparticles are considered one of the promising nanomaterials for biomedical imaging and clinical applications due to their tunable properties, biocompatibility and multimodal imaging ability. In this review, we summarize the synthesis and functionalization of organosilica nanoparticles with a particular focus on their importance in biomedical imaging. By their high fluorescence intensity and unique photostability, organosilica nanoparticles provide capabilities for high-resolution and long-term imaging for in vivo, mesoscopic and microscopic applications. In addition, surface modifications of organosilica nanoparticles control cellular interactions, facilitating the accurate monitoring of cellular uptake, mitochondrial activity and endosomal sorting. Incorporating recent progress and experimental results, this review summarizes the multiformity and extensive prospects of organosilica nanoparticle-based imaging modalities and offers perspectives on future development in nanoparticle-driven biomedical imaging and therapeutic strategies.

Scanning electron microscope (SEM) observation in low vacuum can overcome the issue of charge-up at the specimen surface, allowing for the observation of insulating samples without sample pretreatment. The ultra-variable-pressure detector (UVD) was developed as a secondary electron (SE) detector for the low-vacuum observation in SEM. It works by collecting the light signal released from the collision between SEs and gas molecules. In this study, we propose a simple method using a stainless-steel sphere to characterize the feature of UVD signal in low-vacuum SEM and compare it with the traditional Everhart-Thornley (E-T) detector in normal SEM. The UVD signal showed characteristic features, namely a two-round-peak feature in the profile, which is different from that of E-T detector. Through experiment and simulation, we revealed that at higher vacuum levels (as a few Pa), SEs provide the primary contribution to the UVD signal, exhibiting a profile similar to that of the E-T signal. As the vacuum deteriorates, as 30 Pa, the main contribution to the UVD signal shifts from SEs to low-energy backscattered electrons (BSEs). Our finding indicates that by tuning the chamber pressure, we can vary the UVD image between SE and low-energy BSE features.

Compact soft-X-ray emission spectroscopy (SXES) instrument, which was first applied to transmission electron microscope, was recently applied to scanning electron microscope and electron-probe microanalyzer, which improved the practical applicability of SXES as a tool investigating chemical bonding state of elements in bulk materials. Intensity profiles of Al-L, B-K and Si-L emission spectra which directly reflect the partial density of state of valence band (VB) were explained. Those energy positions are affected by core-level shift (chemical shift; CS) and a change of density of state (DOS) of VB, for example a bandgap formation. Those VB DOS measurements combined with electron-beam scanning technique can conduct a chemical bond mapping of a bulk material. It was presented that L-emission spectra of 3d transition-metal elements gives DOS+CS information in Lα,β emission, dielectric information in Lℓ,η, and the number of 3d electrons in the integrated intensity ratio of Lα,β/(Lα,β+ Lℓ,η). Since the electron-beam excited SXES experiment for bulk specimens can control the self-absorption effect, L-absorption profile of 3d-TM elements is obtainable from L-emission measurements by changing the accelerating voltage. Furthermore, CB information can be obtained from SXES spectra of semiconductor materials, Si and diamond cases were presented, by using the self-absorption effect on the background intensity of bremsstrahlung (BS) caused by electron-beam irradiation of the specimen.

In the fabrication of semiconductor devices, increased yield is achieved using Scanning Electron Microscopes (SEM) to measure and inspect circuit patterns. With recent decreasing scale and increasing complexity of semiconductor circuit patterns, it has become increasingly difficult to recognize patterns accurately using rule-based image processing methods. As such, we propose a method that uses semi-supervised learning for segmentation processing, to recognize which pattern level each pixel represents. With existing methods, the pseudo-labels used for training were not accurate enough, and there were issues such as inconsistent recognition of repeated-pattern layouts and mixed-up results in large unmarked areas distant from the pattern contour. Accordingly, the proposed method is able to perform highly accurate segmentation with the design of new types of loss for evaluating consistency in pattern structure at various scales. When compared with Unimatch and CAC, which are well-known high-performance segmentation methods, the accuracy relative to visual identification increased dramatically, from 10-12% to 100%. In quantitative evaluation using mean Intersection-over-Union (mIoU) at the pixel level, mean values also increased from a range between 0.45 and 0.65 to over 0.94, confirming that the proposed method is effective.

This paper provides an overview of phonon measurement using electron energy loss spectroscopy (EELS) in the electron microscope, with polar cubic boron nitride (c-BN) and nonpolar diamond crystals as representative examples. Differential scattering cross-sections for phonon creation and annihilation are reviewed, highlighting the influence of crystal polarity under kinematical and dynamical scattering conditions. The temperature dependence of EELS intensity is examined, with local absolute temperature evaluated by analysing the ratio of phonon annihilation to creation intensities. Practical aspects and challenges associated with phonon measurement in EELS are also discussed, together with future perspectives in this evolving field.

Aberration correctors are essential for achieving high-resolution imaging in advanced electron microscopy. However, their complexity and cost have limited their integration into conventional scanning electron microscopes (SEMs), particularly in low-voltage applications. In this study, we present a wire aberration corrector that utilizes symmetrically arranged current lines to generate multipole fields. The corrector was implemented in a cold field emission SEM equipped with a bright-field STEM detector and operated at 30 kV. Experimental results demonstrate successful generation of quadrupole to dodecapole fields, effective correction of spherical aberration, and improved imaging of carbon multilayers. These findings demonstrate that wire correctors offer a compact and cost-effective means to enhance imaging performance in standard SEM systems, and the underlying principle could be adapted for other electron microscopy platforms such as TEM or STEM.

The development of radiation tolerant materials is of technological importance for establishing safe operating systems in the nuclear industry, from power generation to the immobilization of high-level radioactive waste. Harsh radiation environments generate interstitials and vacancies in materials, and their accumulation leads to structural changes, including order-to-disorder phase transformations and amorphization. These structural changes are induced locally on an atomic scale; therefore, transmission electron microscopy is a useful technique for analyzing radiation effects in materials. In addition, the strong interaction between matter and electrons enables the detection of weak signals associated with phase transformations, such as diffuse scattering and halo rings. This article provides an overview of radiation-induced amorphous structures in materials consisting of light elements, such as boron carbide and silicon oxycarbide, as well as the short-range ordered structure that appears during an order-to-disorder phase transformation in fluorite structural derivatives.

As interest in fast real-space frame-rate scanning transmission electron microscopy for both structural and functional characterization of materials increases, so does the need for precise and fast electron detection techniques. Electron counting, with monolithic, segmented, or 4D detectors, has been explored for many years. Recent studies have shown that a retrofittable signal digitizer for a monolithic or segmented detector can be a sustainable and accessible way to enhance the performance of existing detectors, especially for imaging at fast scan speeds. Since such signal digitization uses a threshold on the gradient of the detector signal to identify electron events, appropriate threshold choice is key. Previously, this threshold has been set manually by the operator and is therefore inherently susceptible to human bias. In this work, we introduce an auto-thresholding approach for electron counting to determine the optimal threshold by maximizing the difference in identified counts from a stream with real electron events and a stream with only noise. This leads to easier operation, increased throughput and eliminates human bias in signal digitization. When pixel dwell time becomes shorter than scintillator response time, digitization of the detector signal is needed to avoid artefacts in STEM images. Optimizing the threshold for this digitization process automatically is crucial to achieve high-quality quantitative digitized images, free of human bias for what threshold yields the best digitization.

Histological examination using optical microscopy is essential in life sciences and diagnostic medicine, particularly for formalin-fixed paraffin-embedded (FFPE) tissue sections stained with hematoxylin and eosin or 3,3'-diaminobenzidine. However, conventional electron microscopy faces challenges, such as sample destruction, complex processing and difficulty in correlating light and electron microscopy images. The NanoSuit method overcomes these limitations by forming an ultrathin protective membrane that enhances conductivity and preserves hydrated tissue architecture, enabling high-resolution scanning electron microscopy imaging. In this study, we applied NanoSuit-correlative light and electron microscopy (CLEM) to FFPE sections to assess its potential for non-destructive and reversible electron microscopy characterization. Using NanoSuit-CLEM, we successfully visualized endothelial structures, amyloid deposits, sarcomeres, mitochondria, bacteria, viruses and foreign body deposits in FFPE sections. Energy-dispersive X-ray spectrometry further facilitated elemental analysis of foreign materials. These findings demonstrate that NanoSuit-CLEM allows for the precise visualization of ultrastructural details in FFPE sections without requiring new equipment. This method holds promise for advancing pathology by improving diagnostic accuracy and enabling multimodal tissue analysis.