Microscopy and Microanalysis最新文献

Atom probe tomography (APT) is commonly used to study solute clustering and precipitation in materials. However, standard techniques used to identify and characterize clusters within atom probe data, such as the density-based spatial clustering applications with noise (DBSCAN), often underperform with respect to small clusters. This is a limitation of density-based cluster identification algorithms, due to their dependence on the parameter Nmin, an arbitrary lower limit placed on detectable cluster sizes. Therefore, this article attempts to consider the characterization of clustering in atom probe data as an outlier detection problem of which k-nearest neighbors local outlier factor and learnable unified neighborhood-based anomaly ranking algorithms were tested against a simulated dataset and compared to the standard method. The decision score output of the algorithms was then auto thresholded by the Karcher mean to remove human bias. Each of the major models tested outperforms DBSCAN for cluster sizes of <25 atoms but underperforms for sizes >30 atoms using simulated data. However, the new combined k-nearest neighbors (k-NN) and DBSCAN method presented was able to perform well at all cluster sizes. The combined k-NN and seven methods are presented as a new approach to identifying clusters in APT.

We report application of the knife-edge technique at the sharp edges of WS2 and MoS2 monolayer flakes for lateral and axial resolution assessment in all three modalities of nonlinear laser scanning microscopy: two-photon excited fluorescence (TPEF), second- and third-harmonic generation (SHG, THG) imaging. This technique provides a high signal-to-noise ratio, no photobleaching effect and shows good agreement with standard resolution measurement techniques. Furthermore, we assessed both the lateral resolution in TPEF imaging modality and the axial resolution in SHG and THG imaging modality directly via the full-width at half maximum parameter of the corresponding Gaussian distribution. We comprehensively analyzed the factors influencing the resolution, such as the numerical aperture, the excitation wavelength and the refractive index of the embedding medium for the different imaging modalities. Glycerin was identified as the optimal embedding medium for achieving resolutions closest to the theoretical limit. The proposed use of WS2 and MoS2 monolayer flakes emerged as promising tools for characterization of nonlinear imaging systems.

While multislice electron ptychography can provide thermal vibration limited resolution and structural information in 3D, it relies on properly selecting many intertwined acquisition and computational parameters. Here, we outline a methodology for selecting acquisition parameters to enable robust ptychographic reconstructions. We develop two physically informed metrics, areal oversampling and Ronchigram magnification, to describe the selection of these parameters in multislice ptychography. Through simulations, we comprehensively evaluate the validity of these two metrics over a broad range of conditions and show that they accurately guide reconstruction success. Further, we validate these conclusions with experimental ptychographic data and demonstrate close agreement between trends in simulated and experimental data. Using these metrics, we achieve experimental multislice reconstructions at a scan step of 2.1Å/px, enabling large field-of-view, data-efficient reconstructions. These experimental design principles enable the routine and robust use of multislice ptychography for 3D characterization of materials at the atomic scale.

Electron probe microanalysis (EPMA) is a powerful tool for chemical characterization of materials on a microscopic scale. However, EPMA has the drawback that its information volume has a spatial extent of some 100 nm to a few µm. With the introduction of new electron sources, i.e., Schottky Thermal Field and Cold Field Emitter, where the electron beam is focused down to a few nm, measurements can be nowadays performed on the sub-micrometer scale. The goal of the work is to reveal the chemical composition of structures smaller than the excitation volume. New strategies are presented where the acquisition is performed at different positions on the sample and as a scan across a fine structure by using one or more single beam energies. Besides the well-known Monte-Carlo simulation, a deterministic model is also used. The deterministic model is based on moment equations of the Boltzmann equation. Inverse modeling is presented for several case studies. Due to the highly complex nonlinearity of the inverse model, an ill-posed and well-posed problem is shown as well. Finally, the method is extended to reconstruct 2D structures, i.e., rectangular shaped particles, with heterogeneous composition on lateral and depth scale.

Cryo-transfer stations are essential tools in the field of cryo-electron microscopy, enabling the safe transfer of frozen vitreous samples between different stages of the workflow. However, existing cryo-transfer stations are typically configured for only the two most popular sample holder geometries and are not commercially available for all electron microscopes. Additionally, they are expensive and difficult to customize, which limits their accessibility and adaptability for research laboratories. Here, we present a new modular cryo-transfer station that addresses these limitations. The station is composed entirely of 3D-printed and off the shelf parts, allowing it to be reconfigured to a fit variety of microscopes and experimental protocols. We describe the design and construction of the station and report on the results of testing the cryo-transfer station, including its ability to maintain cryogenic temperatures and transfer frozen vitreous samples as demonstrated by vibrational spectroscopy. Our findings demonstrate that the cryo-transfer station performs comparably to existing commercial models, while offering greater accessibility and customizability. The design for the station is open source to encourage other groups to replicate and build on this development. We hope that this project will increase access to cryo-transfer stations for researchers in a variety of disciplines with nonstandard equipment.

Zinc is a critical ion for a large number of cellular functions. In the central nervous system, zinc ions are involved in synaptic transmission. Therefore, zinc homeostasis is essential, and cells have developed a variety of mechanisms to control cellular zinc concentration, including the zincosome formation. Alterations of free zinc levels have been associated with brain dysfunction and are present in many illnesses and syndromes. Astrocytes are implicated in the maintenance of the neuronal milleu and brain homeostasis. In this work, we have analyzed the combination of direct (TSQ) and indirect (autometallography) zinc detection methods to increase sensitivity for studying zinc uptake by rat astrocytes in vitro. Zincosome formation was visualized with the zinc fluorochrome TSQ by light microscopy. Additionally, we improved both zinc precipitation and cellular fixation methods to preserve zinc ions and make them suitable for autometallography development. Our tests pinpointed paraformaldehyde and sodium sulfide as the more adequate methods for cellular fixation and zinc precipitation, respectively. TSQ incubation and pH of the fixative were shown to be crucial for autometallography. Using this improved method, we visualized the zinc content of zincosomes at the ultrastructural level both as silver autometallographic precipitates and as electrodense sulfide-osmium zinc precipitates.

Nanoscale dislocation loops formed by irradiation can significantly contribute to both irradiation hardening and embrittlement of materials when subjected to extreme nuclear reactor environments. This study explores the application of weak-beam dark-field (WBDF) scanning transmission electron microscopy (STEM) methods for quantitative irradiation-induced defect analysis in crystalline materials, with a specific focus on dislocation loop imaging and analysis. A high-purity Fe-5 wt% Cr model alloy was irradiated with 8 MeV Fe2+ ions at 450°C to a fluence of 8.8 × 1019 m-2, inducing dislocation loops for analysis. While transmission electron microscopy (TEM) has traditionally been the primary tool for dislocation imaging, recent advancements in STEM technology have reignited interest in using STEM for defect imaging. This study introduces and compares three WBDF STEM methods, demonstrating their effectiveness in suppressing background contrasts, isolating defect information for dislocation loop type classification, providing finer dislocation line images for small loop analysis, and presenting inside-outside contrast for identifying loop nature. Experimental findings indicate that WBDF STEM methods surpass traditional TEM approaches, yielding clearer and more detailed images of dislocation loops. The study concludes by discussing the potential applications of WBDF STEM techniques in defect analysis, emphasizing their adaptability across various material systems beyond nuclear materials.

This study investigated the morphological characteristics of scales in six Cyprinion species, using light and scanning electron microscopy focusing on key features such as scale type, key scales, lateral line scales, radius/radii, rostral margin, focus, circuli, lepidonts, tubercles, and scale indices. The research analyzed the scales using ultramicroscopy and light microscopy imaging, categorizing them based on size classes and body regions. The morphological variations in scale characteristics were examined across different species, regions, and size classes. Notable findings included the tetra-sectioned form of scales, representing a unique characteristic of the Cyprinion genus. Morphological changes in scale features were observed with fish growth, particularly in the overall shape, focus shape, and size. Quantitative analysis revealed variations in average relative scale length and width among different species, regions, and size classes. The study utilized canonical discriminant analysis for multivariate assessment, classifying the species into distinct groups based on morphometric indices. The findings contribute to the understanding of scale morphology in Cyprinion species and exploring morphological variation between the examined species.

Quantifying light elements such as carbon, nitrogen, and oxygen in a transmission electron microscope (TEM) is a challenging however essential task in biology, materials, or earth and planetary sciences. We have developed an approach that allows precise quantification by energy-dispersive X-ray spectroscopy (EDXS), using sensitive windowless silicon drift detectors and homemade Python routines for hyperspectral data processing. K-factors were determined using wedge-shaped focused ion beam sections. To correct for X-ray absorption within the sample, the sample mass thickness is determined by the-revisited-two-lines method (Morris, 1980). No beam current measurement is required. Applying this method to the K and L lines of iron, we found that the tabulated mass absorption coefficient at the energy of the iron L lines was too low. This is due to X-ray self-absorption at the iron edge. Using reference material, we experimentally determined an absorption coefficient that gave the expected results. We then analyzed the complex phyllosilicate mixture of the Orgueil meteorite. We show that the N/C ratio of organics can be obtained with an accuracy better than 5 at.% and that oxygen can be quantified accurately enough to infer the hydroxyl content of phyllosilicates.

Optimization of user-defined parameters (Dmax, Nmin, order (K)) in the Density-based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, used to characterize nanoclusters in Al-0.9% Mg-1.0% Si-0.3% Cu (mass %), was conducted. Ten combinations of parameters with a given K were considered for samples naturally aged (NA) and preaged (PA) at 100°C. We confirmed four types of unphysical clusters, artificially formed, by analyzing composition with size, atomic density, and atomic arrangement inside clusters. The optimum combinations minimizing those unphysical clusters were obtained for both NA and PA samples. Meanwhile, to evaluate the reliability of the optimum combination, volume rendering and isosurfacing were performed. As a result, regions of high solute concentration were confirmed, and those regions are in good agreement with the position of the clusters obtained by applying the optimum combination in DBSCAN. Furthermore, by comparing the optimum combinations with the fixed parameters widely used until now, we showed that for each dataset, considering independent parameters obtained in the same method is desirable rather than using fixed parameters. Consequently, an idea of determining the algorithm parameters for characterizing the nanoclusters in Al-Mg-Si(-Cu) alloys was introduced.