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Respiratory X-ray imaging enhanced by phase contrast has shown improved airway visualization in animal models. Limitations in current X-ray technology have nevertheless hindered clinical translation, leaving the potential clinical impact an open question. Here, we explore phase-contrast chest radiography in a realistic in silico framework. Specifically, we use preprocessed virtual patients to generate in silico chest radiographs by Fresnel-diffraction simulations of X-ray wave propagation. Following a reader study conducted with clinical radiologists, we predict that phase-contrast edge enhancement will have a negligible impact on improving solitary pulmonary nodule detection (6 to 20 mm). However, edge enhancement of bronchial walls visualizes small airways (<2 mm), which are invisible in conventional radiography. Our results show that phase-contrast chest radiography could play a future role in observing small-airway obstruction (e.g., relevant for asthma or early-stage chronic obstructive pulmonary disease), which cannot be directly visualized using current clinical methods, thereby motivating the experimental development needed for clinical translation. Finally, we discuss quantitative requirements on distances and X-ray source/detector specifications for clinical implementation of phase-contrast chest radiography.

Characterizing relationships between Zn2+, insulin, and insulin vesicles is of vital importance to the study of pancreatic beta cells. However, the precise content of Zn2+ and the specific location of insulin inside insulin vesicles are not clear, which hinders a thorough understanding of the insulin secretion process and diseases caused by blood sugar dysregulation. Here, we demonstrated the colocalization of Zn2+ and insulin in both single extracellular insulin vesicles and pancreatic beta cells by using an X-ray scanning coherent diffraction imaging (ptychography) technique. We also analyzed the elemental Zn2+ and Ca2+ contents of insulin vesicles using electron microscopy and energy dispersive spectroscopy (EDS) mapping. We found that the presence of Zn2+ is an important characteristic that can be used to distinguish insulin vesicles from other types of vesicles in pancreatic beta cells and that the content of Zn2+ is proportional to the size of insulin vesicles. By using dual-energy contrast X-ray microscopy and scanning transmission X-ray microscopy (STXM) image stacks, we observed that insulin accumulates in the off-center position of extracellular insulin vesicles. Furthermore, the spatial distribution of insulin vesicles and their colocalization with other organelles inside pancreatic beta cells were demonstrated using three-dimensional (3D) imaging by combining X-ray ptychography and an equally sloped tomography (EST) algorithm. This study describes a powerful method to univocally describe the location and quantitative analysis of intracellular insulin, which will be of great significance to the study of diabetes and other blood sugar diseases.

Phase retrieval is an important optimization problem that occurs, for example, in the analysis of coherent diffraction patterns from isolated proteins. All iterative algorithms employed for phase retrieval in this context require some a priori knowledge of the object, usually in the form of a support that describes the extent of the particle. Phase retrieval is a time-consuming task that can often fail, particularly if the support is too loose or of bad quality. This paper presents a neural network that can produce low-resolution estimates of the phased object in a fraction of the time it takes for a full phase retrieval. It can also successfully be used as support for further analysis. Our network is trained on simulated data from biological macromolecules and is thus tailored to the type of data seen in a typical CDI experiment. Other approaches to support finding require very accurate data without missing regions or the full phase-retrieval algorithm to be run for a long time. Our network could speed up offline analysis and provide real-time feedback during data collection.

Laser powder bed fusion is a metal additive manufacturing technique that has received significant scientific and industrial attention over the past decades. However, the quality and reproducibility of parts manufactured by this technique is still a problem. Overcoming this issue requires an understanding of multiple complex physical phenomena which occur simultaneously during the process. This work illustrates a powerful new technique which synchronizes high-speed x-ray imaging with high-speed infrared imaging to study laser powder bed fusion processes in real time. Using this technique, we demonstrate the simultaneous observation of multiple phenomena including three-dimensional melt pool visualization, vapor plume dynamics, spatter formation, thermal history, and point cooling rates. The paired observation of these dynamic phenomena is critical to understanding the fundamentals of laser powder bed fusion, and the overall impact of process parameters on print quality.

An experimental procedure for transmission X-ray ghost imaging using synchrotron light is presented. Hard X-rays from an undulator were divided by a beamsplitter to produce two copies of a speckled incident beam. Both beams were simultaneously measured on an indirect pixellated detector and the intensity correlation between the two copies was used to retrieve the ghost image of samples placed in one of the two beams, without measuring the samples directly. Aiming at future practical uses of X-ray ghost imaging, the authors discuss details regarding data acquisition, image reconstruction strategies and measure the point-spread function of the ghost-imaging system. This approach may become relevant for applications of ghost imaging with X-ray sources such as undulators in storage rings, free-electron lasers and lower-coherence laboratory facilities.

Speckle-tracking X-ray imaging is an attractive candidate for dynamic X-ray imaging owing to its flexible setup and simultaneous yields of phase, transmission and scattering images. However, traditional speckle-tracking imaging methods suffer from phase distortion at locations with abrupt changes in density, which is always the case for real samples, limiting the applications of the speckle-tracking X-ray imaging method. In this paper, we report a deep-learning based method which can achieve dynamic X-ray speckle-tracking imaging with high-accuracy phase retrieval. The calibration results of a phantom show that the profile of the retrieved phase is highly consistent with the theoretical one. Experiments of polyurethane foaming demonstrated that the proposed method revealed the evolution of the complicated microstructure of the bubbles accurately. The proposed method is a promising solution for dynamic X-ray imaging with high-accuracy phase retrieval, and has extensive applications in metrology and quantitative analysis of dynamics in material science, physics, chemistry and biomedicine.

In the past few years, X-ray phase-contrast and dark-field imaging have evolved to be invaluable tools for non-destructive sample visualisation, delivering information inaccessible by conventional absorption imaging. X-ray phase-sensing techniques are furthermore increasingly used for at-wavelength metrology and optics characterisation. One of the latest additions to the group of differential phase-contrast methods is the X-ray speckle-based technique. It has drawn significant attention due to its simple and flexible experimental arrangement, cost-effectiveness and multimodal character, amongst others. Since its first demonstration at highly brilliant synchrotron sources, the method has seen rapid development, including the translation to polychromatic laboratory sources and extension to higher-energy X-rays. Recently, different advanced acquisition schemes have been proposed to tackle some of the main limitations of previous implementations. Current applications of the speckle-based method range from optics characterisation and wavefront measurement to biomedical imaging and materials science. This review provides an overview of the state of the art of the X-ray speckle-based technique. Its basic principles and different experimental implementations as well as the the latest advances and applications are illustrated. In the end, an outlook for anticipated future developments of this promising technique is given.

Full-penetration laser beam welding is characterized by a weld seam whose depth equals the material thickness. It is associated with a stable capillary and is therefore widely used for welding of sheet metal components. The realization of lightweight concepts in car body production requires the application of high-strength aluminum alloys that contain magnesium as an alloying element, which significantly influences the evaporation temperature and pressure. This change of the evaporation processes influences the geometry of the capillary and therefore its absorptance. In order to quantify the influence of magnesium on the capillary, their geometries were captured by means of high-speed synchrotron X-ray imaging during the welding process of the aluminum alloys AA1050A (Al99.5), AA5754 (AlMg3) and AA6016 (AlSi1.2Mg0.4). The 3D-geometries of the capillaries were reconstructed from the intensity distribution in the recorded X-ray images and their absorptance of the incident laser beam was determined by the analysis of the reconstructed 3D-geometry with a raytracing algorithm. The results presented in this paper capture for the first time the influence of the magnesium content in high-strength aluminum alloys on the aspect ratio of the capillary, which explains the reduced absorptance in case of full-penetration laser beam welding of aluminum alloys with a high content of volatile elements. In order to improve the absorptance in full-penetration welding, these findings provide the information required for the deduction of new optimization approaches.

Spattering has been a problem in metal processing involving high-power lasers, like laser welding, machining, and recently, additive manufacturing. Limited by the capabilities of in situ diagnostic techniques, typically imaging with visible light or laboratory x-ray sources, a comprehensive understanding of the laser-spattering phenomenon, particularly the extremely fast spatters, has not been achieved yet. Here, using MHz single-pulse synchrotron-x-ray imaging, we probe the spattering behavior of Ti-6Al-4V with micrometer spatial resolution and subnanosecond temporal resolution. Combining direct experimental observations, quantitative image analysis, as well as numerical simulations, our study unravels a novel mechanism of laser spattering: The bulk explosion of a tonguelike protrusion forming on the front keyhole wall leads to the ligamentation of molten metal at the keyhole rims and the subsequent spattering. Our study confirms the critical role of melt and vapor flow in the laser-spattering process and opens a door to manufacturing spatter- and defect-free metal parts via precise control of keyhole dynamics.