The Magid® D-ROC® GPD820 Lightweight NitriX® Palm-Coated Work Glove is the lightest weight ANSI Cut Level 5 glove on the market, delivering superior grip and longer wear-life. The GPD820 is perfect for jobs with laceration hazards along with heavy oil or coolant exposure. Visit Magid at Booth #806.

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The only glove to provide the highest level of cut protection with bare-hand feel now comes in two palm coatings. The D-ROC® GPD800 (polyurethane palm coating) and the new GPD820 (NitriX® Grip Technology palm coating) offer superior comfort, dexterity and grip with maximum level of cut protection around the entire glove.

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Product information is provided by manufacturers. This publication has not independently tested manufacturers' products and cannot assume responsibility for the validity of product claims.

Thirsty Buddha™ Soda joins Buddha Brands™ portfolio of healthy, plant-based products including popular Thirsty Buddha® Coconut Water and Hungry Buddha® Bars. 

Bush's new flavor adds a white chicken chili to its portfolio, offering an easy way for chili lovers to make homemade chili in under 30 minutes with just three simple steps.  

So currently (excuse the terrible schematic graphics) this is what I have: FIOS Router -----[WIRED via Ethernet] ----> Netgear Orbi Mesh ---------> Apple TV box wifi'ed to Netgear Orbi FIOS's new "cable box" wifi'ed to Netgear Orbi (or maybe...

Magic Cactus’ formulation features 2mg of THC, 4mg of CBG, and 6mg of CBD; a “2-4-6” ratio for what Locarni describes as an “approachable, session-able ‘buzz’” where consumers control the consumption experience.

Children's Geographies; 08/01/2021
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Children's Geographies; 06/01/2022
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Children's Geographies; 02/01/2024
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Children's Geographies; 08/01/2024
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The Contextual House, by LO Design, stands as both a tribute to Philadelphia's architectural heritage and a bold statement of contemporary design.

What would it take to build a world where every pregnant person in this country had the rights, resources, and respect they needed to decide what to do with their pregnancy, whether to continue it or not? That world that we want to build is what’s possible with this election and the organizing that must […]

The post Imagining a World Where Reproductive Justice is For Everyone was curated by information for practice.

In this Clever episode, Lisa Donohoe and Brynn Gelbard discuss how Londubh Studio's bold maximalist surface art transforms unique interiors.

Space is around us transforms the Kyano apartment in Athens into a sleek, multifunctional space that blends history with contemporary design.

In the 1980s, Prince wrote one of the Bangles' biggest hits, 'Manic Monday.' Now, The Prince Estate has released the demo version of the track as part of the artist's posthumous album, Originals.

US scientists have reaffirmed the benefits of eating walnuts in a new study. Specialists from the University of California at Davis conducted a series of experiments on a group of male mice diagnosed with prostate cancer. The mice were divided into three diet groups. The first group did not consume walnuts, the second group received walnuts, and the third one was fed with walnut oil. The experiment showed that the development of the tumor and malignant cells significantly slowed among the rodents in the second and the third groups. According to Natural News, the scientists explained the success of the experiment with the content of powerful phytonutrients in raw walnuts. This natural product contains that inhibit cancer cells and prevent them from developing.Just two handfuls of walnuts every day reduces the risk of cancer by almost 50 percent, the scientists said.Furthermore, walnut oil reduces the amount of harmful cholesterol in blood and increases insulin sensitivity, which helps fight heart disease and reduces the risk of diabetes. For example, one study found that overweight adults with type 2 diabetes who consumed just one-quarter cup of walnuts daily reduced their fasting insulin levels in just a few months' time compared to those on non-walnut diets. It is believed that walnuts can shrink levels of the hormone IGF-1, known to play a key role in development of both prostate and breast cancer, Natural News says.Thanks to their omega-3 fat content, walnuts are often the subjects of cancer-preventive studies. However, one should be cautious with eating them as walnuts are a high calorie product. For example, just 2.6 ounces of walnuts is about 482 calories, which may - in some people - contribute to an excess of stored fat. Health benefits of walnuts have been known since time immemorial. Hippocrates and Avicenna mentioned them in the treatment of various diseases. In addition, the ancients thought that they stimulate mental activity. Anna Protsenko, a nutritionist, told MedPulse.ru. "Walnuts contain a great deal of minerals," the expert explains. "They include iron, copper, cobalt, potassium, sodium, phosphorus, magnesium, calcium, and iodine. Many of them are antioxidants. In addition, walnuts contain unsaturated fatty acids, more than 20 amino acids, and vitamins A, E, B, P and C. By the way, they contain nearly 50 times more vitamin C than citrus, and 8 times more than black currants. In addition, walnuts are rich in protein.

EKM, the software solutions provider for simplified managed print, remote service automation, and anything-as-a-service (XaaS) subscription enablement, has entered into an international partnership with Global Document Lifecycle Solutions Integrator, @DOCS, an end-to-end provider for document, records, print and visitor management solutions.

Imaging scaffolds composed of designed protein cages fused to designed ankyrin repeat proteins (DARPins) have enabled the structure determination of small proteins by cryogenic electron microscopy (cryo-EM). One particularly well characterized scaffold type is a symmetric tetrahedral assembly composed of 24 subunits, 12 A and 12 B, which has three cargo-binding DARPins positioned on each vertex. Here, the X-ray crystal structure of a representative tetrahedral scaffold in the apo state is reported at 3.8 Å resolution. The X-ray crystal structure complements recent cryo-EM findings on a closely related scaffold, while also suggesting potential utility for crystallographic investigations. As observed in this crystal structure, one of the three DARPins, which serve as modular adaptors for binding diverse `cargo' proteins, present on each of the vertices is oriented towards a large solvent channel. The crystal lattice is unusually porous, suggesting that it may be possible to soak crystals of the scaffold with small (≤30 kDa) protein cargo ligands and subsequently determine cage–cargo structures via X-ray crystallography. The results suggest the possibility that cryo-EM scaffolds may be repurposed for structure determination by X-ray crystallography, thus extending the utility of electron-microscopy scaffold designs for alternative structural biology applications.

A neutron far-field interferometer is under development at NIST with the aim of enabling a multi-scale measurement combining the best of small-angle neutron scattering (SANS) and neutron imaging and tomography. We use the close relationship between SANS, ultra-SANS, spin-echo SANS and dark-field imaging and measurements of monodisperse spheres as a validation metric, highlighting the strengths and weaknesses of each of these neutron techniques.

The article presents a non-invasive nanoscale imaging technique that can be used in screening crystallization conditions for protein micro- and nanocrystals.

The continued advancement of complex materials often requires a deeper understanding of the structure–function relationship across many length scales, which quickly becomes an arduous task when multiple measurements are required to characterize hierarchical and inherently heterogeneous materials. Therefore, there are benefits in the simultaneous characterization of multiple length scales. At the National Institute of Standards and Technology, a new neutron far-field interferometer is under development that aims to enable a multi-scale measurement combining the best of small-angle neutron scattering (SANS) and neutron imaging and tomography. Spatially resolved structural information on the same length scales as SANS (0.001–1 µm) and ultra-small-angle neutron scattering (USANS, 0.1–10 µm) will be collected via dark-field imaging simultaneously with regular attenuation radiography (>10 µm). The dark field is analogous to the polarization loss measured in spin-echo SANS (SESANS) and is related to isotropic SANS through a Hankel transform. Therefore, we use this close relationship and analyze results from SANS, USANS, SESANS and dark-field imaging of monodisperse spheres as a validation metric for the interferometry measurements. The results also highlight the strengths and weaknesses of these neutron techniques for both steady-state and pulsed neutron sources. Finally, we present an example of the value added by the spatial resolution enabled by dark-field imaging in the study of more complex heterogeneous materials. This information would otherwise be lost in other small-angle scattering measurements averaged over the sample.

The Photoelectron-Related Image and Nano-Spectroscopy (PRINS) endstation located at the Taiwan Photon Source beamline 27A2 houses a photoelectron momentum microscope capable of performing direct-space imaging, momentum-space imaging and photoemission spectroscopy with position sensitivity. Here, the performance of this microscope is demonstrated using two in-house photon sources – an Hg lamp and He(I) radiation – on a standard checkerboard-patterned specimen and an Au(111) single crystal, respectively. By analyzing the intensity profile of the edge of the Au patterns, the Rashba-splitting of the Au(111) Shockley surface state at 300 K, and the photoelectron intensity across the Fermi edge at 80 K, the spatial, momentum and energy resolution were estimated to be 50 nm, 0.0172 Å−1 and 26 meV, respectively. Additionally, it is shown that the band structures acquired in either constant energy contour mode or momentum-resolved photoemission spectroscopy mode were in close agreement.

X-ray diffraction imaging (XDI) is utilized for visualizing the structures of non-crystalline particles in material sciences and biology. In the structural analysis, phase-retrieval (PR) algorithms are applied to the diffraction amplitude data alone to reconstruct the electron density map of a specimen particle projected along the direction of the incident X-rays. However, PR calculations may not lead to good convergence because of a lack of diffraction patterns in small-angle regions and Poisson noise in X-ray detection. Therefore, the PR calculation is still a bottleneck for the efficient application of XDI in the structural analyses of non-crystalline particles. For screening maps from hundreds of trial PR calculations, we have been using a score and measuring the similarity between a pair of retrieved maps. Empirically, probable maps approximating the particle structures gave a score smaller than a threshold value, but the reasons for the effectiveness of the score are still unclear. In this study, the score is characterized in terms of the phase differences between the structure factors of the retrieved maps, the usefulness of the score in screening the maps retrieved from experimental diffraction patterns is demonstrated, and the effective resolution of similarity-score-selected maps is discussed.

In X-ray diffraction imaging (XDI), electron density maps of a targeted particle are reconstructed computationally from the diffraction pattern alone using phase-retrieval (PR) algorithms. However, the PR calculations sometimes fail to yield realistic electron density maps that approximate the structure of the particle. This occurs due to the absence of structure amplitudes at and near the zero-scattering angle and the presence of Poisson noise in weak diffraction patterns. Consequently, the PR calculation becomes a bottleneck for XDI structure analyses. Here, a protocol to efficiently yield realistic maps is proposed. The protocol is based on the empirical observation that realistic maps tend to yield low similarity scores, as suggested in our prior study [Sekiguchi et al. (2017), J. Synchrotron Rad. 24, 1024–1038]. Among independently and concurrently executed PR calculations, the protocol modifies all maps using the electron-density maps exhibiting low similarity scores. This approach, along with a new protocol for estimating particle shape, improved the probability of obtaining realistic maps for diffraction patterns from various aggregates of colloidal gold particles, as compared with PR calculations performed without the protocol. Consequently, the protocol has the potential to reduce computational costs in PR calculations and enable efficient XDI structure analysis of non-crystalline particles using synchrotron X-rays and X-ray free-electron laser pulses.

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

Various X-ray techniques are employed to investigate specimens in diverse fields. Generally, scattering and absorption/emission processes occur due to the interaction of X-rays with matter. The output signals from these processes contain structural information and the electronic structure of specimens, respectively. The combination of complementary X-ray techniques improves the understanding of complex systems holistically. In this context, we introduce a multiplex imaging instrument that can collect small-/wide-angle X-ray diffraction and X-ray emission spectra simultaneously to investigate morphological information with nanoscale resolution, crystal arrangement at the atomic scale and the electronic structure of specimens.

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation–matter interactions in these applications.

Despite the increased brilliance of the new generation synchrotron sources, there is still a challenge with high-resolution scanning of very thick and absorbing samples, such as a whole mouse brain stained with heavy elements, and, extending further, brains of primates. Samples are typically cut into smaller parts, to ensure a sufficient X-ray transmission, and scanned separately. Compared with the standard tomography setup where the sample would be cut into many pillars, the laminographic geometry operates with slab-shaped sections significantly reducing the number of sample parts to be prepared, the cutting damage and data stitching problems. In this work, a laminography pipeline for imaging large samples (>1 cm) at micrometre resolution is presented. The implementation includes a low-cost instrument setup installed at the 2-BM micro-CT beamline of the Advanced Photon Source. Additionally, sample mounting, scanning techniques, data stitching procedures, a fast reconstruction algorithm with low computational complexity, and accelerated reconstruction on multi-GPU systems for processing large-scale datasets are presented. The applicability of the whole laminography pipeline was demonstrated by imaging four sequential slabs throughout an entire mouse brain sample stained with osmium, in total generating approximately 12 TB of raw data for reconstruction.

Nanoscale structural and electronic heterogeneities are prevalent in condensed matter physics. Investigating these heterogeneities in 3D has become an important task for understanding material properties. To provide a tool to unravel the connection between nanoscale heterogeneity and macroscopic emergent properties in magnetic materials, scanning transmission X-ray microscopy (STXM) is combined with X-ray magnetic circular dichroism. A vector tomography algorithm has been developed to reconstruct the full 3D magnetic vector field without any prior noise assumptions or knowledge about the sample. Two tomographic scans around the vertical axis are acquired on single-crystalline Nd2Fe14B pillars tilted at two different angles, with 2D STXM projections recorded using a focused 120 nm X-ray beam with left and right circular polarization. Image alignment and iterative registration have been implemented based on the 2D STXM projections for the two tilts. Dichroic projections obtained from difference images are used for the tomographic reconstruction to obtain the 3D magnetization distribution at the nanoscale.

Understanding the correlation between chemical and microstructural properties is critical for unraveling the fundamental relationship between materials chemistry and physical structures that can benefit materials science and engineering. Here, we demonstrate novel in situ correlative imaging of the X-ray Compton scattering computed tomography (XCS-CT) technique for studying this fundamental relationship. XCS-CT can image light elements that do not usually exhibit strong signals using other X-ray characterization techniques. This paper describes the XCS-CT setup and data analysis method for calculating the valence electron momentum density and lithium-ion concentration, and provides two examples of spatially and temporally resolved chemical properties inside batteries in 3D. XCS-CT was applied to study two types of rechargeable lithium batteries in standard coin cell casings: (1) a lithium-ion battery containing a cathode of bespoke microstructure and liquid electrolyte, and (2) a solid-state battery containing a solid-polymer electrolyte. The XCS-CT technique is beneficial to a wide variety of materials and systems to map chemical composition changes in 3D structures.

Signal-to-noise ratio and spatial resolution are quantitatively analysed in the context of in-line (propagation based) X-ray phase-contrast imaging. It is known that free-space propagation of a coherent X-ray beam from the imaged object to the detector plane, followed by phase retrieval in accordance with Paganin's method, can increase the signal-to-noise in the resultant images without deteriorating the spatial resolution. This results in violation of the noise-resolution uncertainty principle and demonstrates `unreasonable' effectiveness of the method. On the other hand, when the process of free-space propagation is performed in software, using the detected intensity distribution in the object plane, it cannot reproduce the same effectiveness, due to the amplification of photon shot noise. Here, it is shown that the performance of Paganin's method is determined by just two dimensionless parameters: the Fresnel number and the ratio of the real decrement to the imaginary part of the refractive index of the imaged object. The relevant theoretical analysis is performed first, followed by computer simulations and then by a brief test using experimental images collected at a synchrotron beamline. More extensive experimental tests will be presented in the second part of this paper.

X-ray and neutron scattering have long been used for structural characterization of cellulose in plants. Due to averaging over the illuminated sample volume, these measurements traditionally overlooked the compositional and morphological heterogeneity within the sample. Here, a scanning tomographic imaging method is described, using contrast derived from the X-ray scattering intensity, for virtually sectioning the sample to reveal its internal structure at a resolution of a few micrometres. This method provides a means for retrieving the local scattering signal that corresponds to any voxel within the virtual section, enabling characterization of the local structure using traditional data-analysis methods. This is accomplished through tomographic reconstruction of the spatial distribution of a handful of mathematical components identified by non-negative matrix factorization from the large dataset of X-ray scattering intensity. Joint analysis of multiple datasets, to find similarity between voxels by clustering of the decomposed data, could help elucidate systematic differences between samples, such as those expected from genetic modifications, chemical treatments or fungal decay. The spatial distribution of the microfibril angle can also be analyzed, based on the tomographically reconstructed scattering intensity as a function of the azimuthal angle.

A novel insertion device is introduced, designated as the Mango wiggler, designed for synchrotron radiation (SR) imaging that provides a large field of view. This innovative device is constructed from two orthogonal planar wigglers with a small difference in their period lengths, eliciting the phase difference of the magnetic fields to incrementally transitions from 0 to π/2. Such a configuration enlarges the vertical divergence of the light source, as with the horizontal divergence. The appellation `Mango wiggler' derives from the distinctive mango-shaped contour of its radiation field. A comprehensive suite of theoretical analyses and simulations has been executed to elucidate the radiation properties of the Mango wiggler, employing SPECTRA and Mathematica as calculation tools. In conjunction with the ongoing construction of the High Energy Photon Source in Beijing a practical Mango wiggler device has been fabricated for utilization in SR imaging applications. Theoretical analyses were applied to this particular Mango wiggler to yield several theoretical conclusions, and several simulations were performed according to the measured magnetic field results.

The Biomedical Imaging and Therapy facility of the Canadian Light Source comprises two beamlines, which together cover a wide X-ray energy range from 13 keV up to 140 keV. The beamlines were designed with a focus on synchrotron applications in preclinical imaging and veterinary science as well as microbeam radiation therapy. While these remain a major part of the activities of both beamlines, a number of recent upgrades have enhanced the versatility and performance of the beamlines, particularly for high-resolution microtomography experiments. As a result, the user community has been quickly expanding to include researchers in advanced materials, batteries, fuel cells, agriculture, and environmental studies. This article summarizes the beam properties, describes the endstations together with the detector pool, and presents several application cases of the various X-ray imaging techniques available to users.

The advent of diffraction-limited storage rings (DLSRs) has boosted the brilliance or coherent flux by one to two orders of magnitude with respect to the previous generation. One consequence of this brilliance enhancement is an increase in the flux density or number of photons per unit of area and time, which opens new possibilities for the spatiotemporal resolution of X-ray imaging techniques. This paper studies the time-resolved microscopy capabilities of such facilities by benchmarking the ForMAX beamline at the MAX IV storage ring. It is demonstrated that this enhanced flux density using a single harmonic of the source allows micrometre-resolution time-resolved imaging at 2000 tomograms per second and 1.1 MHz 2D acquisition rates using the full dynamic range of the detector system.

A 1D imaging soft X-ray spectrometer installed on the small quantum systems (SQS) scientific instrument of the European XFEL is described. It uses movable cylindrical constant-line-spacing gratings in the Rowland configuration for energy dispersion in the vertical plane, and Wolter optics for simultaneous 1D imaging of the source in the horizontal plane. The soft X-ray fluorescence spectro-imaging capability will be exploited in pump–probe measurements and in investigations of propagation effects and other nonlinear phenomena.

Bragg coherent X-ray diffraction imaging (BCDI) has emerged as a powerful technique for strain imaging and morphology reconstruction of nanometre-scale crystals. However, BCDI often suffers from angular distortions that appear during data acquisition, caused by radiation pressure, heating or imperfect scanning stages. This limits the applicability of BCDI, in particular for small crystals and high-flux X-ray beams. Here, we present a pre-processing algorithm that recovers the 3D datasets from the BCDI dataset measured under the impact of large angular distortions. We systematically investigate the performance of this method for different levels of distortion and find that the algorithm recovers the correct angles for distortions up to 16.4× (1640%) the angular step size dθ = 0.004°. We also show that the angles in a continuous scan can be recovered with high accuracy. As expected, the correction provides marked improvements in the subsequent phase retrieval.

The inherent ambiguity in reconstructed images from coherent diffraction imaging (CDI) poses an intrinsic challenge, as images derived from the same dataset under varying initial conditions often display inconsistencies. This study introduces a method that employs the Noise2Noise approach combined with neural networks to effectively mitigate these ambiguities. We applied this methodology to hundreds of ambiguous reconstructed images retrieved from a single diffraction pattern using a conventional retrieval algorithm. Our results demonstrate that ambiguous features in these reconstructions are effectively treated as inter-reconstruction noise and are significantly reduced. The post-Noise2Noise treated images closely approximate the average and singular value decomposition analysis of various reconstructions, providing consistent and reliable reconstructions.

Full-field transmission X-ray microscopy has been recently implemented at the hard X-ray ROCK–SOLEIL quick-EXAFS beamline, adding micrometre spatial resolution to the second time resolution characterizing the beamline. Benefiting from a beam size versatility due to the beamline focusing optics, full-field hyperspectral XANES imaging has been successfully used at the Fe K-edge for monitoring the pressure-induced spin transition of a 150 µm × 150 µm Fe(o-phen)2(NCS)2 single crystal and the charge of millimetre-sized LiFePO4 battery electrodes. Hyperspectral imaging over 2000 eV has been reported for the simultaneous monitoring of Fe and Cu speciation changes during activation of a FeCu bimetallic catalyst along a millimetre-sized catalyst bed. Strategies of data acquisition and post-data analysis using Jupyter notebooks and multivariate data analysis are presented, and the gain obtained using full-field hyperspectral quick-EXAFS imaging for studies of functional materials under process conditions in comparison with macroscopic information obtained by non-spatially resolved quick-EXAFS techniques is discussed.

The development of hard X-ray nanoprobe techniques has given rise to a number of experimental methods, like nano-XAS, nano-XRD, nano-XRF, ptychography and tomography. Each method has its own unique data processing algorithms. With the increase in data acquisition rate, the large amount of generated data is now a big challenge to these algorithms. In this work, an intuitive, user-friendly software system is introduced to integrate and manage these algorithms; by taking advantage of the loosely coupled, component-based design approach of the system, the data processing speed of the imaging algorithm is enhanced through optimization of the parallelism efficiency. This study provides meaningful solutions to tackle complexity challenges faced in synchrotron data processing.

To date, computed tomography experiments, carried-out at synchrotron radiation facilities worldwide, pose a tremendous challenge in terms of the breadth and complexity of the experimental datasets produced. Furthermore, near real-time three-dimensional reconstruction capabilities are becoming a crucial requirement in order to perform high-quality and result-informed synchrotron imaging experiments, where a large amount of data is collected and processed within a short time window. To address these challenges, we have developed and deployed a synchrotron computed tomography framework designed to automatically process online the experimental data from the synchrotron imaging beamlines, while leveraging the high-performance computing cluster capabilities to accelerate the real-time feedback to the users on their experimental results. We have, further, integrated it within a modern unified national authentication and data management framework, which we have developed and deployed, spanning the entire data lifecycle of a large-scale scientific facility. In this study, the overall architecture, functional modules and workflow design of our synchrotron computed tomography framework are presented in detail. Moreover, the successful integration of the imaging beamlines at the Shanghai Synchrotron Radiation Facility into our scientific computing framework is also detailed, which, ultimately, resulted in accelerating and fully automating their entire data processing pipelines. In fact, when compared with the original three-dimensional tomography reconstruction approaches, the implementation of our synchrotron computed tomography framework led to an acceleration in the experimental data processing capabilities, while maintaining a high level of integration with all the beamline processing software and systems.

Ultra-high-speed synchrotron-based hard X-ray (i.e. above 10 keV) imaging is gaining a growing interest in a number of scientific domains for tracking non-repeatable dynamic phenomena at spatio-temporal microscales. This work describes an optimized indirect X-ray imaging microscope designed to achieve high performance at micrometre pixel size and megahertz acquisition speed. The entire detector optical arrangement has an improved sensitivity within the near-ultraviolet (NUV) part of the emitted spectrum (i.e. 310–430 nm wavelength). When combined with a single-crystal fast-decay scintillator, such as LYSO:Ce (Lu2−xYxSiO5:Ce), it exploits the potential of the NUV light-emitting scintillators. The indirect arrangement of the detector makes it suitable for high-dose applications that require high-energy illumination. This allows for synchrotron single-bunch hard X-ray imaging to be performed with improved true spatial resolution, as herein exemplified through pulsed wire explosion and superheated near-nozzle gasoline injection experiments at a pixel size of 3.2 µm, acquisition rates up to 1.4 MHz and effective exposure time down to 60 ps.

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.

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

Ultrafast, high-intensity X-ray free-electron lasers can perform diffraction imaging of single protein molecules. Various algorithms have been developed to determine the orientation of each single-particle diffraction pattern and reconstruct the 3D diffraction intensity. Most of these algorithms rely on the premise that all diffraction patterns originate from identical protein molecules. However, in actual experiments, diffraction patterns from multiple different molecules may be collected simultaneously. Here, we propose a predicted model-aided one-step classification–multireconstruction algorithm that can handle mixed diffraction patterns from various molecules. The algorithm uses predicted structures of different protein molecules as templates to classify diffraction patterns based on correlation coefficients and determines orientations using a correlation maximization method. Tests on simulated data demonstrated high accuracy and efficiency in classification and reconstruction.

The development of instrumentation as well as applications for megahertz X-ray phase contrast imaging at the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography instrument of the European XFEL are introduced here.

This review focuses on low-dose near-field X-ray speckle phase imaging in the differential mode introducing the existing algorithms with their specifications and comparing their performances under various experimental conditions.

In this work, we showed that the use of ethanol to increase image contrast when imaging cardiac tissue with synchrotron X-ray phase-contrast imaging (X-PCI) leads to heterogeneous tissue shrinkage, which has an impact on the 3D organization of the myocardium.

Developing semiconductor devices requires a fast and reliable source of strain information with high spatial resolution and strain sensitivity. This work investigates the strain in an axially heterostructured 180 nm-diameter GaInP nanowire with InP segments of varying lengths down to 9 nm, simultaneously probing both materials. Scanning X-ray diffraction (XRD) is compared with Bragg projection ptychography (BPP), a fast single-projection method. BPP offers a sufficient spatial resolution to reveal fine details within the largest segments, unlike scanning XRD. The spatial resolution affects the quantitative accuracy of the strain maps, where BPP shows much-improved agreement with an elastic 3D finite element model compared with scanning XRD. The sensitivity of BPP to small deviations from the Bragg condition is systematically investigated. The experimental confirmation of the model suggests that the large lattice mismatch of 1.52% is accommodated without defects.