Dark-field Research Articles

Correcting directional dark field x-ray imaging artefacts using position dependent image deblurring and attenuation removal

In recent years, a novel x-ray imaging modality has emerged that reveals unresolved sample microstructure via a “dark-field image”, which provides complementary information to conventional “bright-field” images, such as attenuation and phase-contrast modalities. This x-ray dark-field signal is produced by unresolved microstructures scattering the x-ray beam resulting in localised image blur. Dark-field retrieval techniques extract this blur to reconstruct a dark-field image. Unfortunately, the presence of non-dark-field blur such as source-size blur or the detector point-spread-function can affect the dark-field retrieval as they also blur the experimental image. In addition, dark-field images can be degraded by the artefacts induced by large intensity gradients from attenuation and propagation-based phase contrast, particularly around sample edges. By measuring any non-dark-field blurring across the image plane and removing it from experimental images, as well as removing attenuation and propagation-based phase contrast, we show that a directional dark-field image can be retrieved with fewer artefacts and more consistent quantitative measures. We present the details of these corrections and provide “before and after” directional dark-field images of samples imaged at a synchrotron source. This paper utilises single-grid directional dark-field imaging, but these corrections have the potential to be broadly applied to other x-ray imaging techniques.

Flame made low Pt loading catalysts supported on different metal oxides for catalytic combustion of CO and CH4

Catalytic combustion is an effective approach to remove air pollutants from various emission sources. For this purpose, supported noble metal catalysts are preferred in commercial applications due to their outstanding catalytic activity for eliminating CO, hydrocarbon compounds and NOx. In this paper, we employ the flame spray pyrolysis method to prepare a series of Pt-based catalysts with four different supports (TiO2, ZrO2, MgO and ZnO) and variable low Pt loadings for catalytic combustion of CO and CH4. The performance of 0.5 Pt/TiO2 is the best in all samples, in which the T90 temperatures are 107 and 500 °C for 90% conversion of CO and CH4, respectively. To examine its thermal stability, a time-on-stream test at 700 °C for 420 min is carried out, resulting in a decrease of about 5% in the final conversion of CH4. The X-ray diffraction results show that TiO2 support is a mixed phase with a major amount of anatase and a small amount of rutile other than a pure phase of ZrO2, MgO and ZnO. Furthermore, X-ray photoelectron spectroscopy analysis and high-angle annular dark-field scanning transmission electron microscopy observation show that when the Pt loading is low, the Pt species exist as highly dispersed single atoms on the surface of the TiO2 support. As the Pt loading gradually increases, the state of the Pt species transitions from single atoms to Pt clusters, resulting in a decrease in dispersion. Ultimately, the Pt can successfully accumulate on the surface of the TiO2 nanoparticles, providing abundant active sites for efficient catalytic combustion reactions.

Machine Learning-Assisted Analysis of Sublingual Microcirculatory Dysfunction for Early Cardiovascular Risk Evaluation and Cardiovascular-Kidney-Metabolic Syndrome Stage in Patients With Type 2 Diabetes Mellitus.

To examine whether sublingual microcirculation can be used as an effective and noninvasive method for assessing cardiovascular, kidney, and metabolic risks in patients with type 2 diabetes mellitus (T2DM). This cross-sectional observational study enrolled 186 patients with T2DM. All patients were evaluated using the Framingham General Cardiovascular Risk Score (FGCRS) and cardiovascular-kidney-metabolic (CKM) syndrome stage. Side-stream dark-field microscopy was used for sublingual microcirculation, including total and perfused vessel density (TVD and PVD). Multiple machine-learning prediction models have been developed for CKM risk and stage assessment in T2DM patients. Receiver operating characteristic (ROC) curves were generated to determine cutoff points. Compared to patients with T2DM, diabetic patients with subclinical atherosclerosis (SA) had a greater CV risk, as measured by the FGCRS, accompanied by markedly decreased microcirculation perfusion. Microcirculatory parameters (TVD and PVD), including carotid intima-media thickness (IMT), brachial-ankle pulse wave velocity (ba-PWV), and FGCRS, were closely associated with SA incidence. Microcirculatory parameters, Index (DMSA screen), and cut-off points were used to screen for SA in patients with T2DM. Furthermore, a new set of four factors identified through machine learning showed optimal sensitivity and specificity for detecting CKM risk in patients with T2DM. Decreased microcirculatory perfusion served as a useful early marker for CKM syndrome risk stratification in patients with T2DM without SA. Sublingual microcirculatory dysfunction is closely correlated with the risk of SA and CKM risk in T2DM patients. Sublingual microcirculation could be a novel tool for assessing the CKM syndrome stage in patients with T2DM.

Morphology and crystallography of E-(Al18Cr2Mg3) nano dispersoids in 7475 Al alloy

The morphology and crystallography of E-(Al18Cr2Mg3) nano dispersoids in 7475 Al alloy have been studied by using transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) and electron tomography (ET). Seven distinct morphologies have been three-dimensionally distinguished at the nanoscale: (i) triangular plates on {111}Al, (ii) hexagonal plates on {111}Al, (iii) rods parallel to <110>Al, (iv) small tetrahedra with {111}Al facets, (v) small octahedra, (vi) spheres and (vii) irregular shapes. Twinning can contribute to the diverse morphologies of E nano dispersoids. The orientation relationships (ORs) between E nano dispersoids and Al matrix have been systematically investigated by selected area electron diffraction (SAED) patterns, HRTEM and matrix calculation. The results from the matrix calculation indicate the absence of clear ORs between E nano dispersoids and Al matrix in 7475 Al alloy.

Debiasing with Diffusion: Probabilistic Reconstruction of Dark Matter Fields from Galaxies with CAMELS

Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter (DM) components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between DM density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in galaxy formation models, which remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct DM fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and subgrid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying DM fields from the given stellar density fields while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes ≈500 times larger than those it was trained on and across different galaxy formation models. The code for reproducing these results can be found at https://github.com/victoriaono/variational-diffusion-cdm ✎.

Modulated crystallographic shear structure in titanium–chromium oxides: their structure and phonon-transport properties

Advancements in phonon engineering have propelled the study of heat conduction within nanostructures, focusing on the wave nature of phonons for thermal conductivity manipulation. This work investigates the annealing-induced structural transformation of titanium–chromium oxide crystals, highlighting a role in modulating thermal conductivity through the regularization of crystallographic shear (CS) plane spacing. Utilizing high-angle annular dark-field scanning transmission electron microscopy and selected-area electron diffraction, a transformation from disordered to ordered arrangements of CS planes was observed through annealing at high temperatures. The thermal conductivity increased following annealing. The variability observed in the spacing of CS planes before annealing implies that phonon Anderson localization might play a role in the changes in thermal conductivity.

Capturing low-concentration benzene: Design and mechanism of high-performance Cu1-Ox,Ny-C single-atom adsorbents

Common adsorbents, such as active carbons, zeolites, and metal–organic frameworks (MOFs), struggle to capture low concentrations of benzene. Single-atom adsorbents (SAAs), boasting exceptional atomic utilization efficiency and precisely tailored electronic structures, offer a promising solution. This study first designed Cu1-Ox,Ny-C SAAs and explored their enhanced benzene adsorption through density functional theory (DFT). Particularly, a crucial link between the SA coordination configuration and its affinity for benzene was established. Next, Cu1-Ox,Ny-C was synthesized from the MOF MIL-101(Cr) and extensively characterized using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and X-ray absorption fine structure (XAFS) spectroscopy, etc. to determine the coordination configuration of Cu single atoms. Finally, a thorough evaluation of the Cu1-Ox,Ny-C’ capacity and stability was conducted. Theoretical analysis revealed that Cu single atoms within the Ox,Ny-C matrix act as the primary adsorption sites for benzene. Notably, O and N atoms work synergistically: oxygen atoms promote adsorption, while nitrogen atoms mainly stabilize single-atom sites. Cu1-Ox,Ny-C was successfully synthesized, and characterization revealed that Cu1-O2,N2(trans)-C and Cu1-O3,N1-C were the dominant coordination configurations. Remarkably, despite a fourfold decrease in specific surface area compared to MIL-101(Cr), Cu1-Ox,Ny-C exhibited a threefold increase in chemisorption capacity for low-concentration benzene. Moreover, it exhibits excellent resistance to H2O and can be effectively reused. This study demonstrates a valuable strategy for designing and creating highly efficient SAAs for capturing low concentrations of benzene.

Raman microscopy allows to follow internalization, subcellular accumulation and fate of iron oxide nanoparticles in cells

An important issue in the context of both potenial toxicity of iron oxide nanoparticles (IONP) and their medical applications is tracking of the internalization process of these nanomaterials into living cells, as well as their localization and fate within them. The typical methods used for this purpose are transmission electron microscopy, confocal fluorescence microscopy as well as light-scattering techniques including dark-field microscopy and flow cytometry. All the techniques mentioned have their advantages and disadvantages. Among the problems it is necessary to mention complicated sample preparation, difficult interpretation of experimental data requiring qualified and experienced personnel, different behavior of fluorescently labeled IONP comparing to those label-free or finally the lack of possibility of chemical composition characteristics of nanomaterials.The purpose of the present investigation was the assessment of the usefulness of Raman microscopy for the tracking of the internalization of IONP into cells, as well as the optimization of this process. Moreover, the study focused on identification of the potential differences in the cellular fate of superparamagnetic nanoparticles having magnetite and maghemite core.The Raman spectra of U87MG cells which internalized IONP presented additional bands which position depended on the used laser wavelength. They occurred at the wavenumber range 1700–2400 cm−1 for laser 488 nm and below the wavenumber of 800 cm−1 in case of laser 532 nm. The intensity of the mentioned Raman bands was higher for the green laser (532 nm) and their position, was independent and not characteristic on the primary core material of IONP (magnetite, maghemite).The obtained results showed that Raman microscopy is an excellent, non-destructive and objective technique that allows monitoring the process of internalization of IONP into cells and visualizing such nanoparticles and/or their metabolism products within them at low exposure levels. What is more, the process of tracking IONP using the technique may be further improved by using appropriate wavelength and power of the laser source.

Hidden Impurities Generate False Positives in Single Atom Catalyst Imaging.

Single-atom catalysts (SACs) are an emerging class of materials, leveraging maximum atom utilization and distinctive structural and electronic properties to bridge heterogeneous and homogeneous catalysis. Direct imaging methods, such as aberration-corrected high-angle annular dark-field scanning transmission electron microscopy, are commonly applied to confirm the atomic dispersion of active sites. However, interpretations of data from these techniques can be challenging due to simultaneous contributions to intensity from impurities introduced during synthesis processes, as well as any variation in position relative to the focal plane of the electron beam. To address this matter, this paper presents a comprehensive study on two representative SACs containing isolated nickel or copper atoms. Spectroscopic techniques, including X-ray absorption spectroscopy, were employed to prove the high metal dispersion of the catalytic atoms. Employing scanning transmission electron microscopy imaging combined with single-atom-sensitive electron energy loss spectroscopy, we scrutinized thin specimens of the catalysts to provide an unambiguous chemical identification of the observed single-atom species and thereby distinguish impurities from active sites at the single-atom level. Overall, the study underscores the complexity of SACs characterization and establishes the importance of the use of spectroscopy in tandem with imaging at atomic resolution to fully and reliably characterize single-atom catalysts.

High-performance electrocatalyst for PEMFC cathode: Combination of ultra-small platinum nanoparticles and N-doped carbon support

To accelerate the implementation of zero-emission power installations based on proton-exchange membrane fuel cells, it is necessary to maximize the power characteristics of these devices. For this purpose, we have obtained and tested a new N-doped carbon support and a synthesized Pt/C catalyst based on it with a platinum loading of about 37.3 %. A comparison of the degradation resistance of the initial support and the N-doped one has shown greater stability of the latter. At the same time, Raman spectroscopy has confirmed the presence of the C–N bond, which indicates the successful doping of carbon with nitrogen. The resulting Pt/C catalyst based on an N-doped support is characterized by a substantially narrow size dispersion and an ultra-small nanoparticle size of about 2.6 nm. The high-angle annular dark-field scanning transmission electron microscopy images of the synthesized catalyst have confirmed the presence of individual platinum atoms/clusters uniformly distributed over the surface of the support, and their presence is due to nitrogen embedded into the carbon structure. This material is characterized by a 50 m2 gPt-1 larger electrochemically active surface area and a 227 A gPt-1 greater mass activity compared to the commercial JM40 analog (40 % platinum loading). Meanwhile, the electrochemical parameters remaining after the accelerated stress testing are almost 2 times higher than those of JM40. And the power characteristics in the membrane electrode assembly for the catalyst synthesized by the facile one-pot synthesis method are 13 % (575 mW cm-2) higher than those of the commercial analog (500 mW cm-2). The Pt/C catalyst obtained during the research is deemed promising for commercial use in proton-exchange membrane fuel cells.

Correlative Lorentz and Dark Field TEM for Studying Skyrmion-Defect Interactions in van der Waals Ferromagnet Co-doped Fe5GeTe2

Correlative Lorentz and Dark Field TEM for Studying Skyrmion-Defect Interactions in van der Waals Ferromagnet Co-doped Fe5GeTe2

Development and Evaluation of a Noninvasive Microfluidic-Based Paper Analytical Device for Leptospirosis Diagnosis.

Leptospirosis is a re-emerging infectious disease that presents a diagnostic enigma for clinicians with frequent misdiagnosis due to lack of rapid and accurate diagnostic tests, as the current methods are encumbered by inherent limitations. The development of a diagnostic sensor with a sample-in-result-out capability is pivotal for prompt diagnosis. Herein, we developed a microfluidic paper-based analytical device (spin-μPAD) featuring a sample-in-result-out fashion for the detection of Leptospira specific urinary biomarker, sph2 sphingomyelinase, crucial for noninvasive point-of-care testing. Fabrication of paper devices involved precise photolithography techniques, ensuring a high degree of reproducibility and replicability. By optimizing the device's configuration and protein components, a remarkable sensitivity and specificity was achieved for detecting leptospiral sph2 in urine, even at low concentrations down to 1.5 fg/mL, with an assay time of 15 min. Further, the spin-μPAD was validated with 20 clinical samples, suspected of leptospirosis including other febrile illnesses, and compared with gold standard microscopic agglutination test, culture, Lepto IgM ELISA, darkfield microscopy, and Leptocheck WB spot test. In contrast to commercial diagnostic tools, the spin-μPAD was noninvasive, rapid, easy to use, specific, sensitive, and cost-effective. The results highlight the potential of this innovative spin-μPAD for an efficient and dependable approach to noninvasive leptospirosis diagnosis, addressing critical needs in the realms of public health and clinical settings.

Pathogenic Leptospira interrogans in Jos North Abattoir, Nigeria: Occurrence, serology, and molecular characterization

Leptospirosis, a neglected zoonotic disease, adversely affects animal, human health, and socioeconomic conditions, particularly in developing countries like Nigeria. This study aimed to determine the occurrence and molecular identification of pathogenic Leptospira spp. among abattoir workers, cattle, and rats in Jos North, Plateau State, Nigeria. Using a cross-sectional study design, a total of 394 samples were collected, including 149 urine samples from abattoir workers, 125 urine samples from cattle bladders, and 120 bladders from trapped rats. Samples were processed and cultured in Ellinghausen McCullough Johnson Harrison (EMJH) medium and examined under a darkfield microscope. Positive cultures were confirmed using the Microscopic Agglutination Test (MAT) and nested Polymerase Chain Reaction (N-PCR) targeted the 16 S rDNA gene. Results revealed a prevalence of 33.76 % for Leptospira spp. across all samples, with the highest occurrence in abattoir workers (13.96 %), followed by rats (13.45 %), and cattle (6.35 %). The MAT showed L. interrogans serovar Hardjo str. Hardjoprajitno as the most prevalent serotype (41.61 %), followed by L. interrogans serovar Icterohaemorrhagiae str. RGA (34.31 %). N-PCR confirmed the presence of pathogenic Leptospira spp., showing bands of 1200 bp. Phylogenetic analysis of the 16 S rDNA gene sequences revealed close similarities to known pathogenic Leptospira strains from Brazil and the USA. The study underscores the significant public health risk posed by leptospirosis in Jos North and highlights the need for improved diagnostic capabilities, increased awareness, and effective control measures to mitigate the disease burden. Enhanced surveillance and preventive strategies are crucial to protect both animal and human health in the region.

Influence of excess silicon on polytype selection during metal-mediated epitaxy of GaN nanowires

We have examined the origins of polytype selection during metal-mediated molecular-beam epitaxy of GaN nanowires (NWs). High-angle annular dark-field scanning transmission electron microscopy reveals [111]-oriented zinc blende (ZB) NWs and [0001]-oriented wurtzite (WZ) NWs, with SixNy at the interface between individual NWs and the Si (001) substrate. Quantitative energy dispersive x-ray spectroscopy reveals a notably higher Si concentration of 7.0% ± 2.3% in zinc blende (ZB) NWs than 2.3% ± 1.2% in wurtzite (WZ) NWs. Meanwhile, density functional theory calculations show that incorporation of 8 at. % Si on the Ga sublattice inverts the difference in formation energies between WZ and ZB GaN, such that the ZB polytype of GaN is stabilized. This identification of Si and other ZB polytype stabilizers will enable the development of polytype heterostructures in a wide variety of WZ-preferring compounds.

Automatic Defect Detection Instrument for Spherical Surfaces of Optical Elements

In order to realize automatic surface defect detection for large aperture precision spherical optical elements, an automatic surface defect detection instrument has been designed. The instrument consists of a microscopic imaging system, illumination system, motion scanning system, and a software algorithm system. Firstly, a multi-angle channel illumination source and a coaxial illumination source were designed. Bright and dark field images of surface defects were captured by cooperating with an automatic zoom microscope. Then, algorithms for scanning trajectory planning, image stitching, and intelligent defect recognition were designed to achieve full-aperture surface image acquisition and defect quantification detection. The automated defect detection process of the instrument is summarized and introduced. Finally, the experimental platform was constructed, which can work well for the optical elements with a maximum diameter of 400 mm and a relative aperture R/D value of 1. It takes about 15 min to detect an optical element with a diameter of 200 mm in dark-field imaging mode. As a result, the minimum line width of scratch detectable is 2 μm and the minimum diameter of pitting detectable is 4 μm. Clearly, the instrument can realize the automatic detection of surface defects of spherical optical elements, and has the advantages of a high efficiency, stability, reliability, quantification, and data traceability.

Critical microstructural modifications of Cu/Zn/Al2O3 catalyst during CO2 hydrogenation to methanol

This contribution reports the impact of the reaction pressure (1, 10, 20 and 30 bar) on the deactivation of the commercial catalyst Cu/ZnO/Al2O3 during the CO2 hydrogenation to CH3OH. The best performance was obtained at 30 bar with ≈ 30 % of initial CO2 conversion (XCO2) and CH3OH space-time-yield (STYMEOH) of 255 mgMeOH/gcat.h. Although the initial conversion decreased drastically the activity was kept along all the reaction time, ≈ 5 %. The analysis of fresh and post-reaction samples using X-ray Diffraction (XRD), Thermogravimetric Analysis (TGA), Electron Microscopy (SEM-FEG, STEM, HRTEM), and Raman Spectroscopy demonstrated profound microstructural changes, characterized by phase sintering, formation of Cu-aluminate, segregation of phases, an imbalance among Cu-species, as well as the presence of coke. As the catalyst Cu/ZnO/Al2O3 has a particular microstructure, these modifications provoked the loss of the geometric configuration of the active sites, which might also originate a disturbance in the electronic interactions, resulting in activity loss. HRTEM and STEM image (dark field) of the passivated sample showed the presence of crystalline nanostructures (d < 4 nm) attributed to Cu0, surrounded by amorphous phases. STEM images of spent samples also reveals the development of hierarchical and elongated nanostructures spread on all the spent catalysts. This result foresees the co-existence of small nanoparticles (< 5 nm) with large ones in all the catalyst surface, corroborating XRD results. It is noteworthy that the hydrothermal environmental developed inside the reactor originated from the high pressure and the continuous H2O production, both which may favor the phase sintering and aluminate formation.

Elemental distribution and site occupancy in a Co-Ni-Al-Ti-Ta-W superalloy

γ'-precipitate strengthened cobalt-based superalloys show promise for higher temperature-capability over nickel-based superalloys due to higher melting temperatures. This study investigates a multicomponent CoNi-based superalloy with composition of 54Co-30Ni-9Al-1Ta-4Ti-2-W (at.%) in terms of elemental partitioning and site occupancy. Atom probe tomography (APT) reveals preferential partitioning of Ni, Al, Ti, Ta and W to the γ'-precipitate and Co to the γ-matrix. Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and energy dispersive spectrometer (EDS) along the [001] zone axis of γ'-precipitate with L12 structure indicate that Co, Ni substitute at A-sites, whereas Al, Ti, Ta, W prefer the B-sites. Density functional theory (DFT) calculations further confirm the results of partitioning behaviors and site preferences. Clarifying elemental partitioning and site occupancy provides valuable insights into alloy design principles for advanced CoNi-based superalloys.

TensorFlow Hydrodynamics Analysis for Ly-[formula omitted] Simulations

We introduce the Python program THALAS (TensorFlow Hydrodynamics Analysis for Lyman-Alpha Simulations), which maps baryon fields (baryon density, temperature, and velocity) to Lyα optical depth fields in both real space and redshift space. Unlike previous Lyα codes, THALAS is fully differentiable, enabling a wide variety of potential applications for general analysis of hydrodynamical simulations and cosmological inference. To demonstrate THALAS’s capabilities, we apply it to the Lyα forest inversion problem: given a Lyα optical depth field, we reconstruct the corresponding real-space dark matter density field. Such applications are relevant to both cosmological and three-dimensional tomographic analyses of Lyman Alpha forest data.

Direct detection system for full-field nanoscale X-ray diffraction-contrast imaging.

Recent developments in X-ray science provide methods to probe deeply embedded mesoscale grain structures and spatially resolve them using dark field X-ray microscopy (DFXM). Extending this technique to investigate weak diffraction signals such as magnetic systems, quantum materials and thin films prove challenging due to available detection methods and incident X-ray flux at the sample. We present a direct detection method developed in conjunction with KAImaging which focuses on DFXM studies in the hard X-ray range of 10s of keV and above capable of approaching nanoscale resolution. Additionally, we compare this direct detection scheme with routinely used scintillator-based optical detection and achieve an order of magnitude improvement in exposure times allowing for imaging of weakly diffracting ordered systems.

Streak artefact removal in x-ray dark-field computed tomography using a convolutional neural network.

Computed tomography (CT) relies on the attenuation of x-rays, and is, hence, of limited use for weakly attenuating organs of the body, such as the lung. X-ray dark-field (DF) imaging is a recently developed technology that utilizes x-ray optical gratings to enable small-angle scattering as an alternative contrast mechanism. The DF signal provides structural information about the micromorphology of an object, complementary to the conventional attenuation signal. A first human-scale x-ray DF CT has been developed by our group. Despite specialized processing algorithms, reconstructed images remain affected by streaking artifacts, which often hinder image interpretation. In recent years, convolutional neural networks have gained popularity in the field of CT reconstruction, amongst others for streak artefactremoval. Reducing streak artifacts is essential for the optimization of image quality in DF CT, and artefact free images are a prerequisite for potential future clinical application. The purpose of this paper is to demonstrate the feasibility of CNN post-processing for artefact reduction in x-ray DF CT and how multi-rotation scans can serve as a pathway for trainingdata. We employed a supervised deep-learning approach using a three-dimensional dual-frame UNet in order to remove streak artifacts. Required training data were obtained from the experimental x-ray DF CT prototype at our institute. Two different operating modes were used to generate input and corresponding ground truth data sets. Clinically relevant scans at dose-compatible radiation levels were used as input data, and extended scans with substantially fewer artifacts were used as ground truth data. The latter is neither dose-, nor time-compatible and, therefore, unfeasible for clinical imaging ofpatients. The trained CNN was able to greatly reduce streak artifacts in DF CT images. The network was tested against images with entirely different, previously unseen image characteristics. In all cases, CNN processing substantially increased the image quality, which was quantitatively confirmed by increased image quality metrics. Fine details are preserved during processing, despite the output images appearing smoother than the ground truthimages. Our results showcase the potential of a neural network to reduce streak artifacts in x-ray DF CT. The image quality is successfully enhanced in dose-compatible x-ray DF CT, which plays an essential role for the adoption of x-ray DF CT into modern clinicalradiology.