When using bifunctional core@shell catalysts, the stability of both the shell and core–shell interface is crucial for catalytic applications. In the present study, we elucidate the stability of a CuO/ZnO/Al2O3@ZSM-5 core@shell material, used for one-stage synthesis of dimethyl ether from synthesis gas. The catalyst stability was studied in a hierarchical manner by complementary environmental transmission electron microscopy (ETEM), scanning electron microscopy (SEM) and in situ hard X-ray ptychography with a specially designed in situ cell. Both reductive activation and reoxidation were applied. The core–shell interface was found to be stable during reducing and oxidizing treatment at 250°C as observed by ETEM and in situ X-ray ptychography, although strong changes occurred in the core on a 10 nm scale due to the reduction of copper oxide to metallic copper particles. At 350°C, in situ X-ray ptychography indicated the occurrence of structural changes also on the µm scale, i.e. the core material and parts of the shell undergo restructuring. Nevertheless, the crucial core–shell interface required for full bifunctionality appeared to remain stable. This study demonstrates the potential of these correlative in situ microscopy techniques for hierarchically designed catalysts.

Image segmentation is a key process in analyzing biological images. However, it is difficult to detect the differences between foreground and background when the image is unevenly illuminated. The unambiguous segmenting of multi-well plate microscopy images with various uneven illuminations is a challenging problem. Currently, no publicly available method adequately solves these various problems in bright-field multi-well plate images. Here, we propose a new method based on contrast values which removes the need for illumination correction. The presented method is effective enough to distinguish foreground and therefore a model organism (Caenorhabditis elegans) from an unevenly illuminated microscope image. In addition, the method also can solve a variety of problems caused by different uneven illumination scenarios. By applying this methodology across a wide range of multi-well plate microscopy images, we show that our approach can consistently analyze images with uneven illuminations with unparalleled accuracy and successfully solve various problems associated with uneven illumination. It can be used to process the microscopy images captured from multi-well plates and detect experimental subjects from an unevenly illuminated background.

Accuracy of atom probe tomography measurements is strongly degraded by the presence of phases that have different evaporation fields. In particular, when there are perpendicular interfaces to the tip axis in the specimen, layers thicknesses are systematically biased and the resolution is degraded near the interfaces. Based on an analytical model of field evaporated emitter end-form, a new algorithm dedicated to the 3D reconstruction of multilayered samples was developed. Simulations of field evaporation of bilayer were performed to evaluate the effectiveness of the new algorithm. Compared to the standard state-of-the-art reconstruction methods, the present approach provides much more accurate analyzed volume, and the resolution is clearly improved near the interface. The ability of the algorithm to handle experimental data was also demonstrated. It is shown that the standard algorithm applied to the same data can commit an error on the layers thicknesses up to a factor 2. This new method is not constrained by the classical hemispherical specimen shape assumption.

In this study we compare two thermal annealing series of III/V semiconductor heterostructures on Si, where during the first series nitrogen is present in the in situ holder. The second, comparative, measurement is done in a tertiarybutylphosphine (TBP) environment. The sample annealed in a TBP environment shows favorable thermal stability up to 500°C compared to the unstabilized sample, which begins to degrade at less than 300°C. Evaporation of P from the material is tracked qualitatively by measuring the thickness of the sample during thermal annealing with and without stabilization. Finally, we investigate the in situ thermal annealing processes at atomic resolution. Here it is possible to study phase separation as well as the diffusion of As from a Ga(NAsP) quantum well in the surrounding GaP material during thermal annealing. To make these investigations possible we developed an extension for our in situ transmission electron microscopy setup for the safe usage of toxic and pyrophoric III/V semiconductor precursors. A commercially available gas cell and gas supply system were expanded with a gas mixing system, an appropriate toxic gas monitoring system and a gas scrubbing system. These components allow in situ studies of semiconductor growth and annealing under the purity conditions required for these materials.

The formation of a bright-field microscopic image of a transparent phase object is described in terms of elementary geometrical optics. Our approach is based on the premise that the image replicates the intensity distribution (real or virtual) at the front focal plane of the objective. The task is therefore reduced to finding the change in intensity at the focal plane caused by the object. This can be done by ray tracing complemented with the requirement of energy conservation. Despite major simplifications involved in such an analysis, it reproduces some results from the paraxial wave theory. In addition, our analysis suggests two ways of extracting quantitative phase information from bright-field images: by vertically shifting the focal plane (the approach used in the transport-of-intensity analysis) or by varying the angle of illumination. In principle, information thus obtained should allow reconstruction of the object morphology.

With the development of affordable aberration correctors, analytical scanning transmission electron microscopy (STEM) studies of complex interfaces can now be conducted at high spatial resolution at laboratories worldwide. Energy-dispersive X-ray spectroscopy (EDS) in particular has grown in popularity, as it enables elemental mapping over a wide range of ionization energies. However, the interpretation of atomically resolved data is greatly complicated by beam–sample interactions that are often overlooked by novice users. Here we describe the practical factors—namely, sample thickness and the choice of ionization edge—that affect the quantification of a model perovskite oxide interface. Our measurements of the same sample, in regions of different thickness, indicate that interface profiles can vary by as much as 2–5 unit cells, depending on the spectral feature. This finding is supported by multislice simulations, which reveal that on-axis maps of even perfectly abrupt interfaces exhibit significant delocalization. Quantification of thicker samples is further complicated by channeling to heavier sites across the interface, as well as an increased signal background. We show that extreme care must be taken to prepare samples to minimize channeling effects and argue that it may not be possible to extract atomically resolved information from many chemical maps.

Ring artifacts are undesirable and complicate the analysis and interpretation of microstructures in synchrotron X-ray microtomography. Here, we propose a new method to improve the image quality of an object by removing the ring artifacts and investigate the efficiency of this process with tomographic images of a dried Tenebrio molitor. In this method, before the tomographic reconstruction, ring artifacts were identified and located in the sinograms as line artifacts. Then, the identified line artifacts were corrected as single point noise via image processing of the original projections. Eventually, the corresponding line artifacts were removed, resulting in reduced ring artifacts in the reconstructed tomographic images. Simulations verified the efficiency of the proposed method. This method was successfully applied for the structural analysis of the insect T. molitor, showing superior performance in reducing ring artifacts in the tomographic image without noticeable loss of structural information.

Cyclin E1 (CCNE1) is a core component of cell cycle regulation that drives the transition into the S phase. CCNE1 plays critical roles in cell cycle, cell proliferation, and cellular functions. However, the function of CCNE1 in early embryonic development is limited. In the present study, the function and expression of Ccne1 in porcine early parthenotes were examined. Immunostaining experiments showed that CCNE1 localized in the nucleus, starting at the four-cell stage. Knockdown of Ccne1 by double-stranded RNA resulted in the failure of blastocyst formation and induced blastocyst apoptosis. Ccne1 depletion increased expression of the pro-apoptotic gene Bax, and decreased the expression of Oct4 and the rate of inner cell mass (ICM)/trophectoderm formation. The results indicated that CCNE1 affects blastocyst formation by inducing cell apoptosis and ICM formation during porcine embryonic development.

Development of collateral vessels, arteriogenesis, may protect against tissue ischemia, however, quantitative data on this process remain scarce. We have developed a technique for replicating the entire arterial network of ischemic rat hindlimbs in three dimensions (3D) based on vascular casting and automated sequential cryo-imaging. Various dilutions of Batson’s No. 17 with methyl methacrylate were evaluated in healthy rats, with further protocol optimization in ischemic rats. Penetration of the resin into the vascular network greatly depended on dilution; the total length of casted vessels below 75 µm was 13-fold higher at 50% dilution compared with the 10% dilution. Dilutions of 25–30%, with transient clamping of the healthy iliac artery, were optimal for imaging the arterial network in unilateral ischemia. This protocol completely filled the lumina of small arterioles and collateral vessels. These appeared as thin anastomoses in healthy legs and increasingly larger vessels during ligation (median diameter 1 week: 63 µm, 4 weeks: 127 µm). The presented combination of quality casts with high-resolution cryo-imaging enables automated, detailed 3D analysis of collateral adaptation, which furthermore can be combined with co-registered 3D distributions of fluorescent molecular imaging markers reflecting biological activity or perfusion.

Polymer electrolyte fuel cells hold great potential for stationary and mobile applications due to high power density and low operating temperature. However, the structural changes during electrochemical reactions are not well understood. In this article, we detail the development of the sample holder equipped with gas injectors and electric conductors and its application to a membrane electrode assembly of a polymer electrolyte fuel cell. Hydrogen and oxygen gases were simultaneously sprayed on the surfaces of the anode and cathode catalysts of the membrane electrode assembly sample, respectively, and observation of the structural changes in the catalysts were simultaneously carried out along with measurement of the generated voltages.

The recent technological advance of the gas field ion source (GFIS) and its successful integration into systems has renewed the interest in the focused ion beam (FIB) technology. Due to the atomically small source size and the use of light ions, the limitations of the liquid metal ion source are solved as device dimensions are pushed further towards the single-digit nanometer size. Helium and neon ions are the most widely used, but a large portfolio of available ion species is desirable, to allow a wide range of applications. Among argon and hydrogen, $${\rm N}_{2}^{{\plus}} $$ ions offer unique characteristics due to their covalent bond and their use as dopant for various carbon-based materials including diamond. Here, we provide a first look at the $${\rm N}_{2}^{{\plus}} $$ GFIS-FIB enabled imaging of a large selection of microscopic structures, including gold on carbon test specimen, thin metal films on insulator and nanostructured carbon-based devices, which are among the most actively researched materials in the field of nanoelectronics. The results are compared with images acquired by He+ ions, and we show that $${\rm N}_{2}^{{\plus}} $$ GFIS-FIB can offer improved material contrast even at very low imaging dose and is more sensitive to the surface roughness.

An automated procedure has been developed for the reconstruction of field ion microscopy (FIM) data that maintains its atomistic nature. FIM characterizes individual atoms on the specimen’s surface, evolving subject to field evaporation, in a series of two-dimensional (2D) images. Its unique spatial resolution enables direct imaging of crystal defects as small as single vacancies. To fully exploit FIM’s potential, automated analysis tools are required. The reconstruction algorithm developed here relies on minimal assumptions and is sensitive to atomic coordinates of all imaged atoms. It tracks the atoms across a sequence of images, allocating each to its respective crystallographic plane. The result is a highly accurate 3D lattice-resolved reconstruction. The procedure is applied to over 2000 tungsten atoms, including ion-implanted planes. The approach is further adapted to analyze carbides in a steel matrix, demonstrating its applicability to a range of materials. A vast amount of information is collected during the experiment that can underpin advanced analyses such as automated detection of “out of sequence” events, subangstrom surface displacements and defects effects on neighboring atoms. These analyses have the potential to reveal new insights into the field evaporation process and contribute to improving accuracy and scope of 3D FIM and atom probe characterization.

Ceramic matrix composites (CMCs) are structural materials, which have useful properties that combine high strength at high temperatures with moderate toughness. Carbon fibers within a matrix of carbon and silicon carbide, called C/C–SiC, are a particular class of CMC noted for their high oxidation resistance. Here we use a combination of four-point bending and X-ray radiography, to study the mechanical failure of C/C-SiC CMCs. Correlating X-ray radiographic and load/displacement curve data reveals that the fiber bundles act to slow down crack propagation during four-point bending tests. We attribute this to the fact that strain energy is expended in breaking these fibers and in pulling fiber bundles out of the surrounding matrix material. In addition, we find that the local distribution and concentration of SiC plays an important role in reducing the toughness of the material.

Electron tomography has become an essential tool for three-dimensional (3D) characterization of nanomaterials. In recent years, advances have been made in specimen preparation and mounting, acquisition geometries, and reconstruction algorithms. All of these components work together to optimize the resolution and clarity of an electron tomogram. However, one important component of the data-processing has received less attention: the 2D tilt series alignment. This is challenging for a number of reasons, namely because the nature of the data sets and the need to be coherently aligned over the full range of angles. An inaccurate alignment may be difficult to identify, yet can significantly limit the final 3D resolution. In this work, we present an improved center-of-mass alignment model that allows us to overcome discrepancies from unwanted objects that enter the imaging area throughout the tilt series. In particular, we develop an approach to overcome changes in the total mass upon rotation of the imaging area. We apply our approach to accurately recover small Pt nanoparticles embedded in a zeolite that may otherwise go undetected both in the 2D microscopy images and the 3D reconstruction. In addition to this, we highlight the particular effectiveness of the compressed sensing methods with this data set.

Image processing and analysis is an effective tool for monitoring and fault diagnosis of activated sludge (AS) wastewater treatment plants. The AS image comprise of flocs (microbial aggregates) and filamentous bacteria. In this paper, nine different approaches are proposed for image segmentation of phase-contrast microscopic (PCM) images of AS samples. The proposed strategies are assessed for their effectiveness from the perspective of microscopic artifacts associated with PCM. The first approach uses an algorithm that is based on the idea that different color space representation of images other than red-green-blue may have better contrast. The second uses an edge detection approach. The third strategy, employs a clustering algorithm for the segmentation and the fourth applies local adaptive thresholding. The fifth technique is based on texture-based segmentation and the sixth uses watershed algorithm. The seventh adopts a split-and-merge approach. The eighth employs Kittler’s thresholding. Finally, the ninth uses a top-hat and bottom-hat filtering-based technique. The approaches are assessed, and analyzed critically with reference to the artifacts of PCM. Gold approximations of ground truth images are prepared to assess the segmentations. Overall, the edge detection-based approach exhibits the best results in terms of accuracy, and the texture-based algorithm in terms of false negative ratio. The respective scenarios are explained for suitability of edge detection and texture-based algorithms.

Accurately identifying and extracting clusters from atom probe tomography (APT) reconstructions is extremely challenging, yet critical to many applications. Currently, the most prevalent approach to detect clusters is the maximum separation method, a heuristic that relies heavily upon parameters manually chosen by the user. In this work, a new clustering algorithm, Gaussian mixture model Expectation Maximization Algorithm (GEMA), was developed. GEMA utilizes a Gaussian mixture model to probabilistically distinguish clusters from random fluctuations in the matrix. This machine learning approach maximizes the data likelihood via expectation maximization: given atomic positions, the algorithm learns the position, size, and width of each cluster. A key advantage of GEMA is that atoms are probabilistically assigned to clusters, thus reflecting scientifically meaningful uncertainty regarding atoms located near precipitate/matrix interfaces. GEMA outperforms the maximum separation method in cluster detection accuracy when applied to several realistically simulated data sets. Lastly, GEMA was successfully applied to real APT data.

The purpose of this work was to determine whether the morphology of the oral mucosa epithelium (OME) of patients with xerostomia differ from patients without xerostomia. In total, 34 patients with dry eye disease (DED) with or without xerostomia were examined at The Norwegian Dry Eye Disease Clinic with in vivo confocal microscopy of the lower lip. In addition, age- and gender-matched healthy controls (HC) were included. DED patients with xerostomia had a higher superficial to deep backscatter ratio compared with DED patients without xerostomia (p=0.002) and HC (p=0.001). Regression analysis demonstrated that this ratio was related to xerostomia independently of gender and age (p<0.001). Sensitivity and specificity of detecting xerostomia were 0.78 and 0.85, respectively, when using a superficial to deep backscatter ratio cut-off value of 0.995 (p=0.004). The mean nucleus to cytosol backscatter ratio in the superficial OME was lower in patients with xerostomia than in those without xerostomia (p=0.034). In vivo confocal microscopy is a potential tool for evaluating the oral cavity and to assess changes in the OME associated with xerostomia, objectively and quantitatively. The cause of the increased backscatter in the superficial OME in xerostomia, however, remains to be elucidated.

The xenon plasma focused ion beam instrument (PFIB), holds significant promise in expanding the applications of focused ion beams in new technology thrust areas. In this paper, we have explored the operational characteristics of a Tescan FERA3 XMH PFIB instrument with the aim of meeting current and future challenges in the semiconductor industry. A two part approach, with the first part aimed at optimizing the ion column and the second optimizing specimen preparation, has been undertaken. Detailed studies characterizing the ion column, optimizing for high-current/high mill rate activities, have been described to support a better understanding of the PFIB. In addition, a novel single-crystal sacrificial mask method has been developed and implemented for use in the PFIB. Using this combined approach, we have achieved high-quality images with minimal artifacts, while retaining the shorter throughput times of the PFIB. Although the work presented in this paper has been performed on a specific instrument, the authors hope that these studies will provide general insight to direct further improvement of PFIB design and applications.