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Diamond sensors for hard X-ray energy and position resolving measurements at the European XFEL

The diagnostics of X-ray beam properties has a critical importance at the European X-ray Free-Electron Laser facility. Besides existing diagnostic components, utilization of a diamond sensor was proposed to achieve radiation-hard, non-invasive beam position and pulse energy measurements for hard X-rays. In particular, with very hard X-rays, diamond-based sensors become a useful complement to gas-based devices which lose sensitivity due to significantly reduced gas cross-sections. The measurements presented in this work were performed with diamond sensors consisting of an electronic-grade single-crystal chemical-vapor-deposition diamond with position-sensitive resistive electrodes in a duo-lateral configuration. The results show that the diamond sensor delivers pulse-resolved X-ray beam position data at 2.25 MHz with an uncertainty of less than 1% of the beam size. To our knowledge this is the first demonstration of pulse-resolved position measurements at the MHz rate using a transmissive diamond sensor at a free-electron laser facility. It can therefore be a valuable tool for X-ray free-electron lasers, especially for high-repetition-rate machines, enabling applications such as beam-based alignment and intra-pulse-train position feedback.




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Using convolutional neural network denoising to reduce ambiguity in X-ray coherent diffraction imaging

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.




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Comparing single-shot damage thresholds of boron carbide and silicon at the European XFEL

Xray free-electron lasers (XFELs) enable experiments that would have been impractical or impossible at conventional X-ray laser facilities. Indeed, more XFEL facilities are being built and planned, with their aim to deliver larger pulse energies and higher peak brilliance. While seeking to increase the pulse power, it is quintessential to consider the maximum pulse fluence that a grazing-incidence FEL mirror can withstand. To address this issue, several studies were conducted on grazing-incidence damage by soft X-ray FEL pulses at the European XFEL facility. Boron carbide (B4C) coatings on polished silicon substrate were investigated using 1 keV photon energy, similar to the X-ray mirrors currently installed at the soft X-ray beamlines (SASE3). The purpose of this study is to compare the damage threshold of B4C and Si to determine the advantages, tolerance and limits of using B4C coatings.




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Mononuclear binding and catalytic activity of europium(III) and gadolinium(III) at the active site of the model metalloenzyme phosphotriesterase

Lanthanide ions have ideal chemical properties for catalysis, such as hard Lewis acidity, fast ligand-exchange kinetics, high coordination-number preferences and low geometric requirements for coordination. As a result, many small-molecule lanthanide catalysts have been described in the literature. Yet, despite the ability of enzymes to catalyse highly stereoselective reactions under gentle conditions, very few lanthanoenzymes have been investigated. In this work, the mononuclear binding of europium(III) and gadolinium(III) to the active site of a mutant of the model enzyme phosphotriesterase are described using X-ray crystallography at 1.78 and 1.61 Å resolution, respectively. It is also shown that despite coordinating a single non-natural metal cation, the PTE-R18 mutant is still able to maintain esterase activity.




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KINNTREX: a neural network to unveil protein mechanisms from time-resolved X-ray crystallography

Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. The method is named KINNTREX (kinetics-informed NN for time-resolved X-ray crystallography). To validate KINNTREX, multiple realistic scenarios were simulated with increasing levels of complexity. For the simulations, time-resolved X-ray data were generated that mimic data collected from the photocycle of the photoactive yellow protein. KINNTREX only requires the number of intermediates and approximate relaxation times (both obtained from a singular valued decomposition) and does not require an assumption of a candidate mechanism. It successfully predicts a consistent chemical kinetic mechanism, together with difference electron-density maps of the intermediates that appear during the reaction. These features make KINNTREX attractive for tackling a wide range of biomolecular questions. In addition, the versatility of KINNTREX can inspire more NN-based applications to time-resolved data from biological macromolecules obtained by other methods.




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Crystallographic phase identifier of a convolutional self-attention neural network (CPICANN) on powder diffraction patterns

Spectroscopic data, particularly diffraction data, are essential for materials characterization due to their comprehensive crystallographic information. The current crystallographic phase identification, however, is very time consuming. To address this challenge, we have developed a real-time crystallographic phase identifier based on a convolutional self-attention neural network (CPICANN). Trained on 692 190 simulated powder X-ray diffraction (XRD) patterns from 23 073 distinct inorganic crystallographic information files, CPICANN demonstrates superior phase-identification power. Single-phase identification on simulated XRD patterns yields 98.5 and 87.5% accuracies with and without elemental information, respectively, outperforming JADE software (68.2 and 38.7%, respectively). Bi-phase identification on simulated XRD patterns achieves 84.2 and 51.5% accuracies, respectively. In experimental settings, CPICANN achieves an 80% identification accuracy, surpassing JADE software (61%). Integration of CPICANN into XRD refinement software will significantly advance the cutting-edge technology in XRD materials characterization.




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Many locks to one key: N-acetyl­neuraminic acid binding to proteins

Sialic acids play crucial roles in cell surface glycans of both eukaryotic and prokaryotic organisms, mediating various biological processes, including cell–cell interactions, development, immune response, oncogenesis and host–pathogen interactions. This review focuses on the β-anomeric form of N-acetyl­neuraminic acid (Neu5Ac), particularly its binding affinity towards various proteins, as elucidated by solved protein structures. Specifically, we delve into the binding mechanisms of Neu5Ac to proteins involved in sequestering and transporting Neu5Ac in Gram-negative bacteria, with implications for drug design targeting these proteins as antimicrobial agents. Unlike the initial assumptions, structural analyses revealed significant variability in the Neu5Ac binding pockets among proteins, indicating diverse evolutionary origins and binding modes. By comparing these findings with existing structures from other systems, we can effectively highlight the intricate relationship between protein structure and Neu5Ac recognition, emphasizing the need for tailored drug design strategies to inhibit Neu5Ac-binding proteins across bacterial species.




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Phase quantification using deep neural network processing of XRD patterns

Mineral identification and quantification are key to the understanding and, hence, the capacity to predict material properties. The method of choice for mineral quantification is powder X-ray diffraction (XRD), generally using a Rietveld refinement approach. However, a successful Rietveld refinement requires preliminary identification of the phases that make up the sample. This is generally carried out manually, and this task becomes extremely long or virtually impossible in the case of very large datasets such as those from synchrotron X-ray diffraction computed tomography. To circumvent this issue, this article proposes a novel neural network (NN) method for automating phase identification and quantification. An XRD pattern calculation code was used to generate large datasets of synthetic data that are used to train the NN. This approach offers significant advantages, including the ability to construct databases with a substantial number of XRD patterns and the introduction of extensive variability into these patterns. To enhance the performance of the NN, a specifically designed loss function for proportion inference was employed during the training process, offering improved efficiency and stability compared with traditional functions. The NN, trained exclusively with synthetic data, proved its ability to identify and quantify mineral phases on synthetic and real XRD patterns. Trained NN errors were equal to 0.5% for phase quantification on the synthetic test set, and 6% on the experimental data, in a system containing four phases of contrasting crystal structures (calcite, gibbsite, dolomite and hematite). The proposed method is freely available on GitHub and allows for major advances since it can be applied to any dataset, regardless of the mineral phases present.




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High-throughput nanoscale crystallization of di­hydro­pyridine active pharmaceutical ingredients

Single-crystal X-ray diffraction analysis of small molecule active pharmaceutical ingredients is a key technique in the confirmation of molecular connectivity, including absolute stereochemistry, as well as the solid-state form. However, accessing single crystals suitable for X-ray diffraction analysis of an active pharmaceutical ingredient can be experimentally laborious, especially considering the potential for multiple solid-state forms (solvates, hydrates and polymorphs). In recent years, methods for the exploration of experimental crystallization space of small molecules have undergone a `step-change', resulting in new high-throughput techniques becoming available. Here, the application of high-throughput encapsulated nanodroplet crystallization to a series of six di­hydro­pyridines, calcium channel blockers used in the treatment of hypertension related diseases, is described. This approach allowed 288 individual crystallization experiments to be performed in parallel on each molecule, resulting in rapid access to crystals and subsequent crystal structures for all six di­hydro­pyridines, as well as revealing a new solvate polymorph of nifedipine (1,4-dioxane solvate) and the first known solvate of nimodipine (DMSO solvate). This work further demonstrates the power of modern high-throughput crystallization methods in the exploration of the solid-state landscape of active pharmaceutical ingredients to facilitate crystal form discovery and structural analysis by single-crystal X-ray diffraction.




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Development of MHz X-ray phase contrast imaging at the European XFEL

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.




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Texture measurements on quartz single crystals to validate coordinate systems for neutron time-of-flight texture analysis

In crystallographic texture analysis, ensuring that sample directions are preserved from experiment to the resulting orientation distribution is crucial to obtain physical meaning from diffraction data. This work details a procedure to ensure instrument and sample coordinates are consistent when analyzing diffraction data with a Rietveld refinement using the texture analysis software MAUD. A quartz crystal is measured on the HIPPO diffractometer at Los Alamos National Laboratory for this purpose. The methods described here can be applied to any diffraction instrument measuring orientation distributions in polycrystalline materials.




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An electropneumatic cleaning device for piezo-actuator-driven picolitre-droplet dispensers

Recently, we introduced the liquid application method for time-resolved analyses (LAMA). The time-consuming cleaning cycles required for the substrate solution exchange and storage of the sensitive droplet-dispenser nozzles present practical challenges. In this work, a dispenser cleaning system for the semi-automated cleaning of the piezo-actuator-driven picolitre-droplet dispensers required for LAMA is introduced to streamline typical workflows.




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Operation model of a skew-symmetric split-crystal neutron interferometer

The observation of neutron interference using a triple Laue interferometer formed by two separate crystals opens the way to the construction and operation of skew-symmetric interferometers with extended arm separation and length. The specifications necessary for their successful operation are investigated here: most importantly, how the manufacturing tolerance and crystal alignments impact the interference visibility. In contrast with previous studies, both incoherent sources and the three-dimensional operation of the interferometer are considered. It is found that, with a Gaussian Schell model of an incoherent source, the integrated density of the particles leaving the interferometer is the same as that yielded by a coherent Gaussian source having a radius equal to the coherence length.




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INSIGHT: in situ heuristic tool for the efficient reduction of grazing-incidence X-ray scattering data

INSIGHT is a Python-based software tool for processing and reducing 2D grazing-incidence wide- and small-angle X-ray scattering (GIWAXS/GISAXS) data. It offers the geometric transformation of the 2D GIWAXS/GISAXS detector image to reciprocal space, including vectorized and parallelized pixel-wise intensity correction calculations. An explicit focus on efficient data management and batch processing enables full control of large time-resolved synchrotron and laboratory data sets for a detailed analysis of kinetic GIWAXS/GISAXS studies of thin films. It processes data acquired with arbitrarily rotated detectors and performs vertical, horizontal, azimuthal and radial cuts in reciprocal space. It further allows crystallographic indexing and GIWAXS pattern simulation, and provides various plotting and export functionalities. Customized scripting offers a one-step solution to reduce, process, analyze and export findings of large in situ and operando data sets.




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Convolutional neural network approach for the automated identification of in cellulo crystals

In cellulo crystallization is a rare event in nature. Recent advances that have made use of heterologous overexpression can promote the intracellular formation of protein crystals, but new tools are required to detect and characterize these targets in the complex cell environment. The present work makes use of Mask R-CNN, a convolutional neural network (CNN)-based instance segmentation method, for the identification of either single or multi-shaped crystals growing in living insect cells, using conventional bright field images. The algorithm can be rapidly adapted to recognize different targets, with the aim of extracting relevant information to support a semi-automated screening pipeline, in order to aid the development of the intracellular protein crystallization approach.




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The multi-slit very small angle neutron scattering instrument at the China Spallation Neutron Source

A multi-slit very small angle neutron scattering (MS-VSANS) instrument has been finally accepted at the China Spallation Neutron Source (CSNS). It is the first spallation neutron source based VSANS instrument. MS-VSANS has a good signal-to-noise ratio and can cover a wide scattering vector magnitude range from 0.00028 to 1.4 Å−1. In its primary flight path, a combined curved multichannel beam bender and sections of rotary exchange drums are installed to minimize the background downstream of the instrument. An exchangeable multi-slit beam focusing system is integrated into the primary flight path, enabling access to a minimum scattering vector magnitude of 0.00028 Å−1. MS-VSANS has three modes, namely conventional SANS, polarizing SANS and VSANS modes. In the SANS mode, three motorized high-efficiency 3He tube detectors inside the detector tank cover scattering angles from 0.12 to 35° simultaneously. In the polarizing SANS mode, a double-V cavity provides highly polarized neutrons and a high-efficiency 3He polarization analyser allows full polarization analysis. In the VSANS mode, an innovative high-resolution gas electron multiplier detector covers scattering angles from 0.016 to 0.447°. The absolute scattering intensities of a selection of standard samples are obtained using the direct-beam technique; the effectiveness of this method is verified by testing the standard samples and comparing the results with those from a benchmark instrument. The MS-VSANS instrument is designed to be flexible and versatile and all the design goals have been achieved.




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Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating

X-ray reflectometry (XRR) is a powerful tool for probing the structural characteristics of nanoscale films and layered structures, which is an important field of nanotechnology and is often used in semiconductor and optics manufacturing. This study introduces a novel approach for conducting quantitative high-resolution millisecond monochromatic XRR measurements. This is an order of magnitude faster than in previously published work. Quick XRR (qXRR) enables real time and in situ monitoring of nanoscale processes such as thin film formation during spin coating. A record qXRR acquisition time of 1.4 ms is demonstrated for a static gold thin film on a silicon sample. As a second example of this novel approach, dynamic in situ measurements are performed during PMMA spin coating onto silicon wafers and fast fitting of XRR curves using machine learning is demonstrated. This investigation primarily focuses on the evolution of film structure and surface morphology, resolving for the first time with qXRR the initial film thinning via mass transport and also shedding light on later thinning via solvent evaporation. This innovative millisecond qXRR technique is of significance for in situ studies of thin film deposition. It addresses the challenge of following intrinsically fast processes, such as thin film growth of high deposition rate or spin coating. Beyond thin film growth processes, millisecond XRR has implications for resolving fast structural changes such as photostriction or diffusion processes.




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Neural network analysis of neutron and X-ray reflectivity data incorporating prior knowledge

Due to the ambiguity related to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X-ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This ambiguity poses limitations on standard neural networks, constraining the range and number of considered parameters in previous machine learning solutions. To overcome this challenge, a novel training procedure has been designed which incorporates dynamic prior boundaries for each physical parameter as additional inputs to the neural network. In this manner, the neural network can be trained simultaneously on all well-posed subintervals of a larger parameter space in which the inverse problem is underdetermined. During inference, users can flexibly input their own prior knowledge about the physical system to constrain the neural network prediction to distinct target subintervals in the parameter space. The effectiveness of the method is demonstrated in various scenarios, including multilayer structures with a box model parameterization and a physics-inspired special parameterization of the scattering length density profile for a multilayer structure. In contrast to previous methods, this approach scales favourably when increasing the complexity of the inverse problem, working properly even for a five-layer multilayer model and a periodic multilayer model with up to 17 open parameters.




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Novel high-efficiency 2D position-sensitive ZnS:Ag/6LiF scintillator detector for neutron diffraction

Scintillator-based ZnS:Ag/6LiF neutron detectors have been under development at ISIS for more than three decades. Continuous research and development aim to improve detector capabilities, achieve better performance and meet the increasingly demanding requirements set by neutron instruments. As part of this program, a high-efficiency 2D position-sensitive scintillator detector with wavelength-shifting fibres has been developed for neutron-diffraction applications. The detector consists of a double scintillator-fibre layer to improve detection efficiency. Each layer is made up of two orthogonal fibre planes placed between two ZnS:Ag/6LiF scintillator screens. Thin reflective foils are attached to the front and back scintillators of each layer to minimize light cross-talk between layers. The detector has an active area of 192 × 192 mm with a square pixel size of 3 × 3 mm. As part of the development process of the double-layer detector, a single-layer detector was built, together with a prototype detector in which the two layers of the detector could be read out separately. Efficiency calculations and measurements of all three detectors are discussed. The novel double-layer detector has been installed and tested on the SXD diffractometer at ISIS. The detector performance is compared with the current scintillator detectors employed on SXD by studying reference crystal samples. More than a factor of 3 improvement in efficiency is achieved with the double-layer wavelength-shifting-fibre detector. Software routines for further optimizations in spatial resolution and uniformity of response have been implemented and tested for 2D detectors. The methods and results are discussed in this manuscript.




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Phase-contrast neutron imaging compared with wave propagation and McStas simulations

Propagation-based phase contrast, for example in the form of edge enhancement contrast, is well established within X-ray imaging but is not widely used in neutron imaging. This technique can help increase the contrast of low-attenuation samples but may confuse quantitative absorption measurements. Therefore, it is important to understand the experimental parameters that cause and amplify or dampen this effect in order to optimize future experiments properly. Two simulation approaches have been investigated, a wave-based simulation and a particle-based simulation conducted in McStas [Willendrup & Lefmann (2020). J. Neutron Res. 22, 1–16], and they are compared with experimental data. The experiment was done on a sample of metal foils with weakly and strongly neutron absorbing layers, which were measured while varying the rotation angle and propagation distance from the sample. The experimental data show multiple signals: attenuation, phase contrast and reflection. The wave model reproduces the sample attenuation and the phase peaks but it does not reproduce the behavior of these peaks as a function of rotation angle. The McStas simulation agrees better with the experimental data, as it reproduces attenuation, phase peaks and reflection, as well as the change in these signals as a function of rotation angle and distance. This suggests that the McStas simulation approach, where the particle description of the neutron facilitates the incorporation of multiple effects, is the most convenient way of modeling edge enhancement in neutron imaging.




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Neural networks for rapid phase quantification of cultural heritage X-ray powder diffraction data

Recent developments in synchrotron radiation facilities have increased the amount of data generated during acquisitions considerably, requiring fast and efficient data processing techniques. Here, the application of dense neural networks (DNNs) to data treatment of X-ray diffraction computed tomography (XRD-CT) experiments is presented. Processing involves mapping the phases in a tomographic slice by predicting the phase fraction in each individual pixel. DNNs were trained on sets of calculated XRD patterns generated using a Python algorithm developed in-house. An initial Rietveld refinement of the tomographic slice sum pattern provides additional information (peak widths and integrated intensities for each phase) to improve the generation of simulated patterns and make them closer to real data. A grid search was used to optimize the network architecture and demonstrated that a single fully connected dense layer was sufficient to accurately determine phase proportions. This DNN was used on the XRD-CT acquisition of a mock-up and a historical sample of highly heterogeneous multi-layered decoration of a late medieval statue, called `applied brocade'. The phase maps predicted by the DNN were in good agreement with other methods, such as non-negative matrix factorization and serial Rietveld refinements performed with TOPAS, and outperformed them in terms of speed and efficiency. The method was evaluated by regenerating experimental patterns from predictions and using the R-weighted profile as the agreement factor. This assessment allowed us to confirm the accuracy of the results.




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Demonstration of neutron time-of-flight diffraction with an event-mode imaging detector

Neutron diffraction beamlines have traditionally relied on deploying large detector arrays of 3He tubes or neutron-sensitive scintillators coupled with photomultipliers to efficiently probe crystallographic and microstructure information of a given material. Given the large upfront cost of custom-made data acquisition systems and the recent scarcity of 3He, new diffraction beamlines or upgrades to existing ones demand innovative approaches. This paper introduces a novel Timepix3-based event-mode imaging neutron diffraction detector system as well as first results of a silicon powder diffraction measurement made at the HIPPO neutron powder diffractometer at the Los Alamos Neutron Science Center. Notably, these initial measurements were conducted simultaneously with the 3He array on HIPPO, enabling direct comparison. Data reduction for this type of data was implemented in the MAUD code, enabling Rietveld analysis. Results from the Timepix3-based setup and HIPPO were benchmarked against McStas simulations, showing good agreement for peak resolution. With further development, systems such as the one presented here may substantially reduce the cost of detector systems for new neutron instrumentation as well as for upgrades of existing beamlines.




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Resonant neutron scattering lengths

Unlike most of the periodic table, many rare-earth elements display considerable resonant scattering for thermal neutrons. Although this property is accompanied by strong neutron absorption, modern high-intensity neutron sources make diffraction experiments possible with these elements. Computation of scattering intensities is accomplished by fitting the variation in resonant scattering lengths (b0, b' and b'') to a semi-empirical Breit–Wigner formalism, which can be evaluated over the range of neutron energies useful for diffraction, typically E = 10–600 meV; λ = 0.4–2.8 Å (with good extrapolation to longer wavelengths).




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The promise of GaAs 200 in small-angle neutron scattering for higher resolution

The Q resolution in Bonse–Hart double-crystal diffractometers is determined for a given Bragg angle by the value of the crystallographic structure factor. To date, the reflections Si 220 or Si 111 have been used exclusively in neutron scattering, which provide resolutions for triple-bounce crystals of about 2 × 10−5 Å−1 (FWHM). The Darwin width of the GaAs 200 reflection is about a factor of 10 smaller, offering the possibility of a Q resolution of 2 × 10−6 Å−1 provided crystals of sufficient quality are available. This article reports a feasibility study with single-bounce GaAs 200, yielding a Q resolution of 4.6 × 10−6 Å−1, six times superior in comparison with a Si 220 setup.




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Pushing the limits of accessible length scales via a modified Porod analysis in small-angle neutron scattering on ordered systems

Small-angle neutron scattering is a widely used technique to study large-scale structures in bulk samples. The largest accessible length scale in conventional Bragg scattering is determined by the combination of the longest available neutron wavelength and smallest resolvable scattering angle. A method is presented that circumvents this limitation and is able to extract larger length scales from the low-q power-law scattering using a modification of the well known Porod law connecting the scattered intensity of randomly distributed objects to their specific surface area. It is shown that in the special case of a highly aligned domain structure the specific surface area extracted from the modified Porod law can be used to determine specific length scales of the domain structure. The analysis method is applied to study the micrometre-sized domain structure found in the intermediate mixed state of the superconductor niobium. The analysis approach allows the range of accessible length scales to be extended from 1 µm to up to 40 µm using a conventional small-angle neutron scattering setup.




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Multidimensional Rietveld refinement of high-pressure neutron diffraction data of PbNCN

High-pressure neutron powder diffraction data from PbNCN were collected on the high-pressure diffraction beamline SNAP located at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory (Tennessee, USA). The diffraction data were analyzed using the novel method of multidimensional (two dimensions for now, potentially more in the future) Rietveld refinement and, for comparison, employing the conventional Rietveld method. To achieve two-dimensional analysis, a detailed description of the SNAP instrument characteristics was created, serving as an instrument parameter file, and then yielding both cell and spatial parameters as refined under pressure for the first time for solid-state cyanamides/carbodi­imides. The bulk modulus B0 = 25.1 (15) GPa and its derivative B'0 = 11.1 (8) were extracted for PbNCN following the Vinet equation of state. Surprisingly, an internal transition was observed beyond 2.0 (2) GPa, resulting from switching the bond multiplicities (and bending direction) of the NCN2− complex anion. The results were corroborated using electronic structure calculation from first principles, highlighting both local structural and chemical bonding details.




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SUBGROUPS: a computer tool at the Bilbao Crystallographic Server for the study of pseudo-symmetric or distorted structures

SUBGROUPS is a free online program at the Bilbao Crystallographic Server (https://www.cryst.ehu.es/). It permits the exploration of all possible symmetries resulting from the distortion of a higher-symmetry parent structure, provided that the relation between the lattices of the distorted and parent structures is known. The program calculates all the subgroups of the parent space group which comply with this relation. The required minimal input is the space-group information of the parent structure and the relation of the unit cell of the distorted or pseudo-symmetric structure with that of the parent structure. Alternatively, the wavevector(s) observed in the diffraction data characterizing the distortion can be introduced. Additional conditions can be added, including filters related to space-group representations. The program provides very detailed information on all the subgroups, including group–subgroup hierarchy graphs. If a Crystallographic Information Framework (CIF) file of the parent high-symmetry structure is uploaded, the program generates CIF files of the parent structure described under each of the chosen lower symmetries. These CIF files may then be used as starting points for the refinement of the distorted structure under these possible symmetries. They can also be used for density functional theory calculations or for any other type of analysis. The power and efficiency of the program are illustrated with a few examples.




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Pinhole small-angle neutron scattering based approach for desmearing slit ultra-small-angle neutron scattering data

Presented here is an effective approach to desmearing slit ultra-small-angle neutron scattering (USANS) data, based on complementary small-angle neutron scattering (SANS) measurements, leading to a seamless merging of these data sets. The study focuses on the methodological aspects of desmearing USANS data, which can then be presented in the conventional manner of SANS, enabling a broader pool of data analysis methods. The key innovation lies in the use of smeared SANS data for extrapolating slit USANS, offering a self-consistent integrand function for desmearing with Lake's iterative method. The proposed approach is validated through experimental data on porous anodized aluminium oxide membranes, showcasing its applicability and benefits. The findings emphasize the importance of accurate desmearing for merging USANS and SANS data in the crossover q region, which is particularly crucial for complex scattering patterns.




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Electronic angle focusing for neutron time-of-flight powder diffractometers

A neutron time-of-flight (TOF) powder diffractometer with a continuous wide-angle array of detectors can be electronically focused to make a single pseudo-constant wavelength diffraction pattern, thus facilitating angle-dependent intensity corrections. The resulting powder diffraction peak profiles are affected by the neutron source emission profile and resemble the function currently used for TOF diffraction.




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A miniature X-ray diffraction setup on ID20 at the European Synchrotron Radiation Facility

We describe an ultra-compact setup for in situ X-ray diffraction on the inelastic X-ray scattering beamline ID20 at the European Synchrotron Radiation Facility. The main motivation for the design and construction of this setup is the increasing demand for on-the-fly sample characterization, as well as ease of navigation through a sample's phase diagram, for example subjected to high-pressure and/or high-temperature conditions. We provide technical details and demonstrate the performance of the setup.




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Satispay raises EUR 60 million to further drive its service expansion

Italy-based unicorn Satispay has announced...




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XMDS Holding launches XPP to unify payment solutions across Europe

XMDS Holding has launched XPP, a new umbrella organisation...




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Mirakl partners with Mangopay to accelerate development of European marketplaces

Mirakl has announced its partnership with



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Careem Pay introduces instant transfers for customers in Europe

Digital wallet and fintech platform Careem Pay has launched...




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Key Players In the EU Payments Landscape – 2024 Edition

The 2024 'Key Players in the EU Payments Landscape' report by PA EU, Deloitte, and The Paypers ranks key players in EU's payments markets.




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Genome introduces SEPA Instant Transfers for Eurozone payments

Lithuania-based Genome has launched SEPA Instant Transfers,...




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Interview in the mausoleum with relics expert Elizabeth Harper

Elizabeth Harper, a relics expert, at Mountain View Cemetery in Altadena; Credit: John Rabe

John Rabe | Off-Ramp®

"Reach a certain moment in your life, and you discover that your days are spent as much with the dead as they are with the living." – Paul Auster

This has been one of my favorite quotes for a long time. To me it means that when you get older and your friends, relatives, and heroes start dying, you have a choice. You can either stop thinking about them because they're dead, giving up, as it were, the pleasure of their company; or you can keep them in your life. To me, that's not denial; it's being realistic.

So, it makes sense that I felt a kindred spirit with Elizabeth Harper, who keeps the website All the Saints You Should Know, when we met at a beautiful mausoleum at Mountain View Cemetery in Altadena to talk about the history of cemeteries, relics, castrated Italian avuncular mummies, and the best spots in Los Angeles to commune healthily with death.

Elizabeth will be part of the team when Atlas Obscura leads tours of The Cathedral of Our Lady of the Angels on Saturday, July 1. It's billed as "A celebration of life, death, architecture, and the patron saint of Los Angeles."

Here are some highlights of my mausoleum conversation with Elizabeth Harper:

At first glance, she says, all of the tombs are very similar.

And that was one of the things, when we started making modern cemeteries, outside the city lines, they wanted them to be regular and not so expressive and macabre. But people leave little things behind. On a lot of these (crypts), you can see a little emblem of something that was important to them. If they were a Mason or if they served in the Army. I like the (cremains) urns that are shaped like books. I have a friend who is a librarian and she was very taken with the idea of being in a book.

Napoleon instituted the Edict of Saint-Cloud, which mandated that cemeteries must be outside city limits (for health reasons) and must be toned-down (for no good reason).

People did not like the edict. There's a very famous poem called Sepulchers by Ugo Foscolo that was written in protest, that said, essentially, looking upon the graves of strong men strengthens the mind and the spirit.

From Slate: Photographing the Real Bodies of Incorrupt Saints, by Elizabeth Harper

Elizabeth often writes about cemeteries and tombs and sometimes posts photos of bodies, which causes a "certain segment" to assume she has no experience with death, or she wouldn't presume to do such a thing.

What I want to put out there is that we have this pervasive idea that we grieve and move on, and this moving on is very important, and I think there are multiple ways to incorporate the idea of death in your life, to get used to the idea, without forgetting, that's more of a way of memorializing. When I take these pictures, I'm very aware that these are real people, and I think of myself, what I will be one day, and people I love, who are already there.

Make sure to listen to our entire interview in the audio player to hear Elizabeth's 3 top spots in Los Angeles to consider the place of death in our lives, and to hear about poor old Uncle Vincent, a neutered naked mummy in a small town in Italy who has a large fan base.

 

This content is from Southern California Public Radio. View the original story at SCPR.org.




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Adyen supports Tap-to-Pay on iPhone in more European markets

Global financial platform Adyen has announced that it enabled...




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Mollie rolls out Tap to Pay on iPhone for European merchants

Mollie, a financial service provider in Europe, has introduced Tap to Pay on iPhone, enabling businesses to accept contactless payments via the Mollie app.




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EU regulators accept Deutsche Telekom's Czech mobile unit, 02 Czech concessions

"The Commission made binding commitments offered by T-Mobile CZ, CETIN and O2 CZ that will keep the benefits of network sharing whilst removing technical and financial disincentives to unilateral deployments and limiting information exchange, all to the benefit of Czech mobile user," Commission Vice-President Margrethe Vestager said in a statement.




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Reuse of Disposable Medical Masks During Flu Pandemic Not Recommended - Reusing Respirators Is Complicated

Use of protective face coverings will be one of many strategies used to slow or prevent transmission of the flu virus in the event of a pandemic, even though scientific evidence about the effectiveness of inexpensive, disposable medical masks and respirators against influenza is limited.




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New Report on Science Learning at Museums, Zoos, Other Informal Settings

Each year, tens of millions of Americans, young and old, choose to learn about science in informal ways -- by visiting museums and aquariums, attending after-school programs, pursuing personal hobbies, and watching TV documentaries, for example.




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Scientific Evidence Of Health Problems From Past Contamination Of Drinking Water At Camp Lejeune Is Limited And Unlikely To Be Resolved With Further Study

Evidence exists that people who lived or worked at Camp Lejeune Marine Base in North Carolina between the 1950s and 1985 were exposed to the industrial solvents tricholorethylene (TCE) or perchloroethylene (PCE) in their water supply, but strong scientific evidence is not available to determine whether health problems among those exposed are due to the contaminants, says a new report from the National Research Council.




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Report Affirms the Goal of Elimination of Civilian Use of Highly Enriched Uranium and Calls for Step-wise Conversion of Research Reactors Still Using Weapon-grade Uranium Fuel - 50-year Federal Roadmap for Neutron-based Research Recommended

Efforts to convert civilian research reactors from weapon-grade highly enriched uranium (HEU) to low enriched uranium (LEU) fuels are taking significantly longer than anticipated, says a congressionally mandated report from the National Academies of Sciences, Engineering, and Medicine.




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G7 Academies Release Statements on Cultural Heritage, Economic Growth, Neurodegenerative Diseases

Joint statements from the national science academies of the G7 nations were delivered today to the Italian government in advance of the G7 Summit to be held in Taormina, Italy, at the end of May.




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U.S. Has Lost Its Dominance in Highly Intense, Ultrafast Laser Technology to Europe and Asia

The U.S. is losing ground in a second laser revolution of highly intense, ultrafast lasers that have broad applications in manufacturing, medicine, and national security, says a new report from the National Academies of Sciences, Engineering, and Medicine.




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U.S. Department of Transportation Should Revisit Federal Safety Regulations for Liquid Petroleum Gas Distribution Systems, Says New Report

Current federal safety regulations for small distribution systems used for propane and other liquefied petroleum gases (LPGs) should be improved for clarity, efficiency, enforceability, and applicability to risk, says a new report from the National Academies of Sciences, Engineering, and Medicine.




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Reusable Respirators Are an Effective and Viable Option for Protecting Health Care Personnel During Routine Work and Public Health Emergency Response, Says New Report

Half-facepiece reusable elastomeric respirators are an effective and viable option for protecting health care workers from exposure to airborne transmissible contaminants or infectious agents — for example, influenza virus — during day-to-day work or with a sudden or rapid influx of patients, such as during a public health emergency, says a new report from the National Academies of Sciences, Engineering, and Medicine.




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National Academies Completes Review of National Toxicology Program’s Draft Monograph on Fluoride and Neurodevelopmental and Cognitive Effects

Today the National Academies of Sciences, Engineering, and Medicine released its review of the National Toxicology Program’s (NTP) draft monograph Systematic Review of Fluoride Exposure and Neurodevelopmental and Cognitive Health Effects.




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National Academies Complete Review of National Toxicology Program’s Second Draft Monograph on Fluoride Exposure and Neurodevelopmental and Cognitive Effects

The National Academies of Sciences, Engineering, and Medicine released today a review of the National Toxicology Program’s (NTP) second draft of the monograph Systematic Review of Fluoride Exposure and Neurodevelopmental and Cognitive Health Effects.