During the automatic processing of crystallographic diffraction experiments, beamstop shadows are often unaccounted for or only partially masked. As a result of this, outlier reflection intensities are integrated, which is a known issue. Traditional statistical diagnostics have only limited effectiveness in identifying these outliers, here termed Not-Excluded-unMasked-Outliers (NEMOs). The diagnostic tool AUSPEX allows visual inspection of NEMOs, where they form a typical pattern: clusters at the low-resolution end of the AUSPEX plots of intensities or amplitudes versus resolution. To automate NEMO detection, a new algorithm was developed by combining data statistics with a density-based clustering method. This approach demonstrates a promising performance in detecting NEMOs in merged data sets without disrupting existing data-reduction pipelines. Re-refinement results indicate that excluding the identified NEMOs can effectively enhance the quality of subsequent structure-determination steps. This method offers a prospective automated means to assess the efficacy of a beamstop mask, as well as highlighting the potential of modern pattern-recognition techniques for automating outlier exclusion during data processing, facilitating future adaptation to evolving experimental strategies.

A group of three deep-learning tools, referred to collectively as CHiMP (Crystal Hits in My Plate), were created for analysis of micrographs of protein crystallization experiments at the Diamond Light Source (DLS) synchrotron, UK. The first tool, a classification network, assigns images into categories relating to experimental outcomes. The other two tools are networks that perform both object detection and instance segmentation, resulting in masks of individual crystals in the first case and masks of crystallization droplets in addition to crystals in the second case, allowing the positions and sizes of these entities to be recorded. The creation of these tools used transfer learning, where weights from a pre-trained deep-learning network were used as a starting point and repurposed by further training on a relatively small set of data. Two of the tools are now integrated at the VMXi macromolecular crystallography beamline at DLS, where they have the potential to absolve the need for any user input, both for monitoring crystallization experiments and for triggering in situ data collections. The third is being integrated into the XChem fragment-based drug-discovery screening platform, also at DLS, to allow the automatic targeting of acoustic compound dispensing into crystallization droplets.

Serial electron diffraction (SerialED), which applies a snapshot data acquisition strategy for each crystal, was introduced to tackle the problem of radiation damage in the structure determination of beam-sensitive materials by three-dimensional electron diffraction (3DED). The snapshot data acquisition in SerialED can be realized using both transmission and scanning transmission electron microscopes (TEM/STEM). However, the current SerialED workflow based on STEM setups requires special external devices and software, which limits broader adoption. Here, we present a simplified experimental implementation of STEM-based SerialED on Thermo Fisher Scientific STEMs using common proprietary software interfaced through Python scripts to automate data collection. Specifically, we utilize TEM Imaging and Analysis (TIA) scripting and TEM scripting to access the STEM functionalities of the microscope, and DigitalMicrograph scripting to control the camera for snapshot data acquisition. Data analysis adapts the existing workflow using the software CrystFEL, which was developed for serial X-ray crystallography. Our workflow for STEM SerialED can be used on any Gatan or Thermo Fisher Scientific camera. We apply this workflow to collect high-resolution STEM SerialED data from two aluminosilicate zeolites, zeolite Y and ZSM-25. We demonstrate, for the first time, ab initio structure determination through direct methods using STEM SerialED data. Zeolite Y is relatively stable under the electron beam, and STEM SerialED data extend to 0.60 Å. We show that the structural model obtained using STEM SerialED data merged from 358 crystals is nearly identical to that using continuous rotation electron diffraction data from one crystal. This demonstrates that accurate structures can be obtained from STEM SerialED. Zeolite ZSM-25 is very beam-sensitive and has a complex structure. We show that STEM SerialED greatly improves the data resolution of ZSM-25, compared with serial rotation electron diffraction (SerialRED), from 1.50 to 0.90 Å. This allows, for the first time, the use of standard phasing methods, such as direct methods, for the ab initio structure determination of ZSM-25.

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.

This paper uses deep learning to present a proof-of-concept for data-driven chemistry in single-molecule magnets (SMMs). Previous discussions within SMM research have proposed links between molecular structures (crystal structures) and single-molecule magnetic properties; however, these have only interpreted the results. Therefore, this study introduces a data-driven approach to predict the properties of SMM structures using deep learning. The deep-learning model learns the structural features of the SMM molecules by extracting the single-molecule magnetic properties from the 3D coordinates presented in this paper. The model accurately determined whether a molecule was a single-molecule magnet, with an accuracy rate of approximately 70% in predicting the SMM properties. The deep-learning model found SMMs from 20 000 metal complexes extracted from the Cambridge Structural Database. Using deep-learning models for predicting SMM properties and guiding the design of novel molecules is promising.

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules (e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

The large Bunyavirales order includes several families of viruses with a segmented ambisense (−) RNA genome and a cytoplasmic life cycle that starts by synthesizing viral mRNA. The initiation of transcription, which is common to all members, relies on an endonuclease activity that is responsible for cap-snatching. In La Crosse virus, an orthobunyavirus, it has previously been shown that the cap-snatching endonuclease resides in the N-terminal domain of the L protein. Orthobunyaviruses are transmitted by arthropods and cause diseases in cattle. However, California encephalitis virus, La Crosse virus and Jamestown Canyon virus are North American species that can cause encephalitis in humans. No vaccines or antiviral drugs are available. In this study, three known Influenza virus endonuclease inhibitors (DPBA, L-742,001 and baloxavir) were repurposed on the La Crosse virus endonuclease. Their inhibition was evaluated by fluorescence resonance energy transfer and their mode of binding was then assessed by differential scanning fluorimetry and microscale thermophoresis. Finally, two crystallographic structures were obtained in complex with L-742,001 and baloxavir, providing access to the structural determinants of inhibition and offering key information for the further development of Bunyavirales endonuclease inhibitors.

Appreciating that the role of the solute–solvent and other outer-sphere interactions is essential for understanding chemistry and chemical dynamics in solution, experimental approaches are needed to address the structural consequences of these interactions, complementing condensed-matter simulations and coarse-grained theories. High-energy X-ray scattering (HEXS) combined with pair distribution function analysis presents the opportunity to probe these structures directly and to develop quantitative, atomistic models of molecular systems in situ in the solution phase. However, at concentrations relevant to solution-phase chemistry, the total scattering signal is dominated by the bulk solvent, prompting researchers to adopt a differential approach to eliminate this unwanted background. Though similar approaches are well established in quantitative structural studies of macromolecules in solution by small- and wide-angle X-ray scattering (SAXS/WAXS), analogous studies in the HEXS regime—where sub-ångström spatial resolution is achieved—remain underdeveloped, in part due to the lack of a rigorous theoretical description of the experiment. To address this, herein we develop a framework for differential solution scattering experiments conducted at high energies, which includes concepts of the solvent-excluded volume introduced to describe SAXS/WAXS data, as well as concepts from the time-resolved X-ray scattering community. Our theory is supported by numerical simulations and experiment and paves the way for establishing quantitative methods to determine the atomic structures of small molecules in solution with resolution approaching that of crystallography.

Here, the novel technique of extended-range high-energy-resolution fluorescence detection (XR-HERFD) has successfully observed the n = 2 satellite in manganese to a high accuracy. The significance of the satellite signature presented is many hundreds of standard errors and well beyond typical discovery levels of three to six standard errors. This satellite is a sensitive indicator for all manganese-containing materials in condensed matter. The uncertainty in the measurements has been defined, which clearly observes multiple peaks and structure indicative of complex physical quantum-mechanical processes. Theoretical calculations of energy eigenvalues, shake-off probability and Auger rates are also presented, which explain the origin of the satellite from physical n = 2 shake-off processes. The evolution in the intensity of this satellite is measured relative to the full Kα spectrum of manganese to investigate satellite structure, and therefore many-body processes, as a function of incident energy. Results demonstrate that the many-body reduction factor S02 should not be modelled with a constant value as is currently done. This work makes a significant contribution to the challenge of understanding many-body processes and interpreting HERFD or resonant inelastic X-ray scattering spectra in a quantitative manner.

The aberrant fibrillization of huntingtin exon 1 (Httex1) characterized by an expanded polyglutamine (polyQ) tract is a defining feature of Huntington's disease, a neurodegenerative disorder. Recent investigations underscore the involvement of a small EDRK-rich factor 1a (SERF1a) in promoting Httex1 fibrillization through interactions with its N terminus. By establishing an integrated approach with size-exclusion-column-based small- and wide-angle X-ray scattering (SEC-SWAXS), NMR, and molecular simulations using Rosetta, the analysis here reveals a tight binding of two NT17 fragments of Httex1 (comprising the initial 17 amino acids at the N terminus) to the N-terminal region of SERF1a. In contrast, examination of the complex structure of SERF1a with a coiled NT17-polyQ peptide (33 amino acids in total) indicates sparse contacts of the NT17 and polyQ segments with the N-terminal side of SERF1a. Furthermore, the integrated SEC-SWAXS and molecular-simulation analysis suggests that the coiled NT17 segment can transform into a helical conformation when associated with a polyQ segment exhibiting high helical content. Intriguingly, NT17-polyQ peptides with enhanced secondary structures display diminished interactions with SERF1a. This insight into the conformation-dependent binding of NT17 provides clues to a catalytic association mechanism underlying SERF1a's facilitation of Httext1 fibrillization.

X-ray and neutron crystallography, as well as cryogenic electron microscopy (cryo-EM), are the most common methods to obtain atomic structures of biological macromolecules. A feature they all have in common is that, at typical resolutions, the experimental data need to be supplemented by empirical restraints, ensuring that the final structure is chemically reasonable. The restraints are accurate for amino acids and nucleic acids, but often less accurate for substrates, inhibitors, small-molecule ligands and metal sites, for which experimental data are scarce or empirical potentials are harder to formulate. This can be solved using quantum mechanical calculations for a small but interesting part of the structure. Such an approach, called quantum refinement, has been shown to improve structures locally, allow the determination of the protonation and oxidation states of ligands and metals, and discriminate between different interpretations of the structure. Here, we present a new implementation of quantum refinement interfacing the widely used structure-refinement software Phenix and the freely available quantum mechanical software ORCA. Through application to manganese superoxide dismutase and V- and Fe-nitro­genase, we show that the approach works effectively for X-ray and neutron crystal structures, that old results can be reproduced and structural discrimination can be performed. We discuss how the weight factor between the experimental data and the empirical restraints should be selected and how quantum mechanical quality measures such as strain energies should be calculated. We also present an application of quantum refinement to cryo-EM data for particulate methane monooxygenase and show that this may be the method of choice for metal sites in such structures because no accurate empirical restraints are currently available for metals.

MltG, a membrane-bound lytic transglycosyl­ase, has roles in terminating glycan polymerization in peptidoglycan and incorporating glycan chains into the cell wall, making it significant in bacterial cell-wall biosynthesis and remodeling. This study provides the first reported MltG structure from Mycobacterium abscessus (maMltG), a superbug that has high antibiotic resistance. Our structural and biochemical analyses revealed that MltG has a flexible peptidoglycan-binding domain and exists as a monomer in solution. Further, the putative active site of maMltG was disclosed using structural analysis and sequence comparison. Overall, this study contributes to our understanding of the transglycosyl­ation reaction of the MltG family, aiding the design of next-generation antibiotics targeting M. abscessus.

The accuracy of the information in the Protein Data Bank (PDB) is of great importance for the myriad downstream applications that make use of protein structural information. Despite best efforts, the occasional introduction of errors is inevitable, especially where the experimental data are of limited resolution. A novel protein structure validation approach based on spotting inconsistencies between the residue contacts and distances observed in a structural model and those computationally predicted by methods such as AlphaFold2 has previously been established. It is particularly well suited to the detection of register errors. Importantly, this new approach is orthogonal to traditional methods based on stereochemistry or map–model agreement, and is resolution independent. Here, thousands of likely register errors are identified by scanning 3–5 Å resolution structures in the PDB. Unlike most methods, the application of this approach yields suggested corrections to the register of affected regions, which it is shown, even by limited implementation, lead to improved refinement statistics in the vast majority of cases. A few limitations and confounding factors such as fold-switching proteins are characterized, but this approach is expected to have broad application in spotting potential issues in current accessions and, through its implementation and distribution in CCP4, helping to ensure the accuracy of future depositions.

A few real case examples are presented on how to report magnetic structures, with precise step-by-step explanations, following the guidelines of the IUCr Commission on Magnetic Structures [Perez-Mato et al. (2024). Acta Cryst. B80, 219–234]. Four examples have been chosen, illustrating different types of single-k magnetic orders, from the basic case to more complex ones, including odd-harmonics, and one multi-k order. In addition to acquainting researchers with the process of communicating commensurate magnetic structures, these examples also aim to clarify important concepts, which are used throughout the guidelines, such as the transformation to a standard setting of a magnetic space group.

An exhaustive search for missing symmetry was performed for 223 076 entries in the ICSD (2023-2 release). Approximately 0.65% of them can be described with higher symmetry than reported. Out of the identified noncentrosymmetric entries, ∼74% can be described by centrosymmetric space groups; this has implications for compatible physical properties. It is proposed that the information on the correct space group is included in the ICSD.

The mol­ecular and crystal structure of a discrete [Ni8(μ4-OH)6(μ-4-Rpz)12]2− (R = H; pz = pyrazolate anion, C3H3N2−) cluster with an unprecedented, perfectly cubic arrangement of its eight Ni centers is reported, along with its lower-symmetry alkyl-functionalized (R = methyl and n-oct­yl) derivatives. Crystals of the latter two were obtained with two identical counter-ions (Bu4N+), whereas the crystal of the complex with the parent pyrazole ligand has one Me4N+ and one Bu4N+ counter-ion. The methyl derivative incorporates 1,2-di­chloro­ethane solvent mol­ecules in its crystal structure, whereas the other two are solvent-free. The compounds are tetra­butyl­aza­nium tetra­methyl­aza­nium hexa-μ4-hydroxido-dodeca-μ2-pyrazolato-hexa­hedro-octa­nickel, (C16H36N)(C4H12N)[Ni8(C3H3N2)12(OH)6] or (Bu4N)(Me4N)[Ni8(μ4-OH)6(μ-pz)12] (1), bis­(tetra­butyl­aza­nium) hexa-μ4-hydroxido-dodeca-μ2-(4-methyl­pyrazolato)-hexa­hedro-octa­nickel 1,2-di­chloro­ethane 7.196-solvate, (C16H36N)2[Ni8(C4H5N2)12(OH)6]·7.196C2H4Cl2 or (Bu4N)2[Ni8(μ4-OH)6(μ-4-Mepz)12]·7.196(ClCH2CH2Cl) (2), and bis­(tetra­butyl­aza­nium) hexa-μ4-hydroxido-dodeca-μ2-(4-octylpyrazolato)-hexa­hedro-octa­nickel, (C16H36N)2[Ni8(C11H19N2)12(OH)6] or (Bu4N)2[Ni8(μ4-OH)6(μ-4-nOctpz)12] (3). All counter-ions are disordered (with the exception of one Bu4N+ in 3). Some of the octyl chains of 3 (the crystal is twinned by non-merohedry) are also disordered. Various structural features are discussed and contrasted with those of other known [Ni8(μ4-OH)6(μ-4-Rpz)12]2− complexes, including extended three-dimensional metal–organic frameworks. In all three structures, the Ni8 units are lined up in columns.

This paper summarizes brief perspectives on the historic process of establishing an African Crystallographic Association (AfCA) and includes representative references. It covers activities within four arbitrarily selected, approximate time slots, i.e., 1890s–1999, 2000–2013, 2014–2019 and 2020–2023. A genuine attempt is made to include appropriate role players, organizations and accompanying events within these periods. It concludes with the official admission of AfCA as the fifth Regional Associate of the IUCr at the 26th Congress and General Assembly of the IUCr in Melbourne, Australia in 2023.

JUAMI, the joint undertaking for an African materials institute, is a project to build collaborations and materials research capabilities between PhD researchers in Africa, the United States, and the world. Focusing on research-active universities in the East African countries of Kenya, Ethiopia, Tanzania and Uganda, the effort has run a series of schools focused on materials for sustainable energy and materials for sustainable development. These bring together early-career researchers from Africa, the US, and beyond, for two weeks in a close-knit environment. The program includes lectures on cutting-edge research from internationally renowned speakers, highly interactive tutorial lectures on the science behind the research, also from internationally known researchers, and hands-on practicals and team-building exercises that culminate in group proposals from self-formed student teams. The schools have benefited more than 300 early-career students and led to proposals that have received funding and have led to research collaborations and educational non-profits. JUAMI continues and has an ongoing community of alumni who share resources and expertise, and is open to like-minded people who want to join and develop contacts and collaborations internationally.

The synthesis and crystallographic analysis of the title compound, C9H9N3O2S, are reported. The compound crystallizes in the monoclinic space group P21/c, revealing characteristic bond lengths and angles typical of thio­semicarbazone groups. The supra­molecular organization primarily arises from hydrogen bonding and π–π stacking inter­actions, leading to distinctive dimeric formations.

Reaction of Co(NCS)2 with 4-methyl­pyridine N-oxide in methanol leads to the formation of crystals of the title compound, [Co2(NCS)4(C6H7NO)4(CH4O)2] or Co2(NCS)4(4-methyl­pyridine N-oxide)4(methanol)2. The asymmetric unit consist of one CoII cation, two thio­cyanate anions, two 4-methyl­pyridine N-oxide coligands and one methanol mol­ecule in general positions. The H atoms of one of the methyl groups are disordered and were refined using a split model. The CoII cations octa­hedrally coordinate two terminal N-bonded thio­cyanate anions, three 4-methyl­pyridine N-oxide coligands and one methanol mol­ecule. Each two CoII cations are linked by pairs of μ-1,1(O,O)-bridging 4-methyl­pyridine N-oxide coligands into dinuclear units that are located on centers of inversion. Powder X-ray diffraction (PXRD) investigations prove that the title compound is contaminated with a small amount of Co(NCS)2(4-meth­yl­pyridine N-oxide)3. Thermogravimetric investigations reveal that the methanol mol­ecules are removed in the beginning, leading to a compound with the composition Co(NCS)2(4-methyl­pyridine N-oxide), which has been reported in the literature and which is of poor crystallinity.

The reaction of copper(II) oxalate and hexa­methyl­ene­tetra­mine in a deep eutectic solvent made of urea and choline chloride produced crystals of penta­amine­copper(II) dichloride–urea (1/1), [Cu(NH3)5]Cl2·CO(NH2)2, which was characterized by single-crystal X-ray diffraction. The complex contains discrete penta­amine­copper(II) units in a square-based pyramidal geometry. The overall structure of the multi-component crystal is dictated by hydrogen bonding between urea mol­ecules and amine H atoms with chloride anions.

Three organoplatinum(II) complexes bearing natural aryl­olefin and quinoline derivatives, namely, [4-meth­oxy-5-(2-meth­oxy-2-oxoeth­oxy)-2-(prop-2-en-1-yl)phen­yl](quinolin-8-olato)platinum(II), [Pt(C13H15O4)(C9H6NO)], (I), [4-meth­oxy-5-(2-oxo-2-propoxyeth­oxy)-2-(prop-2-en-1-yl)phen­yl](quinoline-2-carboxy­l­ato)platinum(II), [Pt(C15H19O4)(C10H6NO2)], (II), and chlorido­[4-meth­oxy-5-(2-oxo-2-propoxyeth­oxy)-2-(prop-2-en-1-yl)phen­yl](quinoline)­plat­inum(II), [Pt(C15H19O4)Cl(C9H7N)], (III), were synthesized and structurally characterized by IR and 1H NMR spectroscopy, and by single-crystal X-ray diffraction. The results showed that the cyclo­platinated aryl­olefin coordinates with PtII via the carbon atom of the phenyl ring and the C=Colefinic group. The deprotonated 8-hy­droxy­quinoline (C9H6NO) and quinoline-2-carb­oxy­lic acid (C10H6NO2) coordinate with the PtII atom via the N and O atoms in complexes (I) and (II) while the quinoline (C9H7N) coordinates via the N atom in (III). Moreover, the coordinating N atom in complexes (I)–(III) is in the cis position compared to the C=Colefinic group. The crystal packing is characterized by C—H⋯π, C—H⋯O [for (II) and (III)], C—H⋯Cl [for (III) and π–π [for (I)] inter­actions.

The chemical reaction of 4-bromo­benzoyl­chloride and 2-amino­thia­zole in the presence of potassium thio­cyanate yielded a white solid formulated as C15H10BrN3OS2, which consists of 4-bromo­benzamido and 2-benzo­thia­zolyl moieties connected by a thio­urea group. The 4-bromo­benzamido and 2-benzo­thia­zolyl moieties are in a trans conformtion (sometimes also called s-trans due to the single bond) with respect to the N—C bond. The dihedral angle between the mean planes of the 4-bromo­phenyl and the 2-benzo­thia­zolyl units is 10.45 (11)°. The thio­urea moiety, —C—NH—C(=S) —NH— fragment forms a dihedral angle of 8.64 (12)° with the 4-bromo­phenyl ring and is almost coplanar with the 2-benzo­thia­zolyl moiety, with a dihedral angle of 1.94 (11)°. The mol­ecular structure is stabilized by intra­molecular N—H⋯O hydrogen bonds, resulting in the formation of an S(6) ring. In the crystal, pairs of adjacent mol­ecules inter­act via inter­molecular hydrogen bonds of type C—H⋯N, C—H⋯S and N—H⋯S, resulting in mol­ecular layers parallel to the ac plane.

This title compound, C20H26O2, was isolated from the benzene fraction of the stem bark of Staudtia kamerunensis Warb. (Myristicaceae) using column chromatography techniques over silica gel. The compound was fully characterized by single-crystal X-ray diffraction, one and two-dimensional NMR spectroscopy, IR and MS spectrometry. The compound has two fused cyclo­hexane rings attached to a benzene ring, with a carb­oxy­lic acid on C-4. This cyclo­hexene ring has a chair conformation while the other adopts a half-chair conformation. The benzene ring is substituted with a propenyl moiety. The structure is characterized by inter­molecular O—H⋯O hydrogen bonds, two C—H⋯O intra­molecular hydrogen bonds and two C—H⋯π inter­actions. The mol­ecular structure confirms previous studies carried out by spectroscopic techniques.

A new mononuclear complex, penta­aqua­(cucurbit[6]uril-κ2O,O')(nitrato-κ2O,O')praseodymium(III) dinitrate 9.56-hydrate, [Pr(NO3)(CB6)(H2O)5](NO3)2·9.56H2O (1), was obtained as outcome of the hydro­thermal reaction between the macrocyclic ligand cucurbit[6]uril (CB6, C36H36N24O12) with a tenfold excess of Pr(NO3)3·6H2O. Complex 1 crystallizes in the P21/n space group with two crystallographically independent but chemically identical [Pr(CB6)(NO3)(H2O)5]2+ complex cations, four nitrate counter-anions and 19.12 inter­stitial water mol­ecules per asymmetric unit. The nona­coordinated PrIII in 1 are located in the PrO9 coordination environment formed by two carbonyl O atoms from bidentate cucurbit[6]uril units, two oxygen atoms from the bidentate nitrate anion and five water mol­ecules. Considering the differences in Pr—O bond distances and O—Pr—O angles in the coordination spheres, the coordination polyhedrons of the two PrIII atoms can be described as distorted spherical capped square anti­prismatic and muffin polyhedral.

A new quinoline derivative, namely, 6-(di­ethyl­amino)-4-phenyl-2-(pyridin-2-yl)quinoline, C24H23N3 (QP), and its MnII complex aqua-1κO-di-μ-chlorido-1:2κ4Cl:Cl-di­chlorido-1κCl,2κCl-bis­[6-(di­ethyl­amino)-4-phenyl-2-(pyridin-2-yl)quinoline]-1κ2N1,N2;2κ2N1,N2-dimanganese(II), [Mn2Cl4(C24H23N3)2(H2O)] (MnQP), were synthesized. Their compositions have been determined with ESI-MS, IR, and 1H NMR spectroscopy. The crystal-structure determination of MnQP revealed a dinuclear complex with a central four-membered Mn2Cl2 ring. Both MnII atoms bind to an additional Cl atom and to two N atoms of the QP ligand. One MnII atom expands its coordination sphere with an extra water mol­ecule, resulting in a distorted octa­hedral shape. The second MnII atom shows a distorted trigonal–bipyramidal shape. The UV–vis absorption and emission spectra of the examined compounds were studied. Furthermore, when investigating the aggregation-induced emission (AIE) properties, it was found that the fluorescent color changes from blue to green and eventually becomes yellow as the fraction of water in the THF/water mixture increases from 0% to 99%. In particular, these color and intensity changes are most pronounced at a water fraction of 60%. The crystal structure contains disordered solvent mol­ecules, which could not be modeled. The SQUEEZE procedure [Spek (2015). Acta Cryst. C71, 9–18] was used to obtain information on the type and qu­antity of solvent mol­ecules, which resulted in 44 electrons in a void volume of 274 Å3, corresponding to approximately 1.7 mol­ecules of ethanol in the unit cell. These ethanol mol­ecules are not considered in the given chemical formula and other crystal data.

The X-ray crystal structure data of 12-α-fluoro-3β-hy­droxy­olean-28,13β-olide methanol hemisolvate, 2C30H47FO3·CH3OH, (1), and 12-α-fluoro-3β-hy­droxy­taraxer-28,14β-olide methanol hemisolvate, 2C30H47FO3·CH3OH, (2), are described. The fluoro­lactonization of oleanolic acid using SelectfluorTM yielded a mixture of the six-membered δ-lactone (1) and the unusual seven-membered γ-lactone (2) following a 1,2-shift of methyl C-27 from C-14 to C-13.

In the structure of the title salt, {[Ba(μ3-C3H2N3O2)2(μ-H2O)(H2O)]·H2O}n, the barium ion and all three oxygen atoms of the water mol­ecules reside on a mirror plane. The hydrogen atoms of the bridging water and the solvate water mol­ecules are arranged across a mirror plane whereas all atoms of the monodentate aqua ligand are situated on this mirror plane. The distorted ninefold coord­ination of the Ba ions is completed with four nitroso-, two carbonyl- and three aqua-O atoms at the distances of 2.763 (3)–2.961 (4) Å and it is best described as tricapped trigonal prism. The three-dimensional framework structure is formed by face-sharing of the trigonal prisms, via μ-nitroso- and μ-aqua-O atoms, and also by the bridging coordination of the anions via carbonyl-O atoms occupying two out of the three cap positions. The solvate water mol­ecules populate the crystal channels and facilitate a set of four directional hydrogen bonds. The principal Ba–carbamoyl­cyano­nitro­somethanido linkage reveals a rare example of the inherently polar binodal six- and three-coordinated bipartite topology (three-letter notation sit). It suggests that small resonance-stabilized cyano­nitroso anions can be utilized as bridging ligands for the supra­molecular synthesis of MOF solids. Such an outcome may be anti­cipated for a broader range of hard Lewis acidic alkaline earth metal ions, which perfectly match the coordination preferences of highly nucleophilic nitroso-O atoms. Thermal analysis reveals two-stage dehydration of the title compound (383 and 473 K) followed by decomposition with release of CO2, HCN and H2O at 558 K.

This work describes the X-ray structure of orange–red crystals of 2-meth­oxy-5-nitro­aniline, C7H8N2O3. The compound displays concentration-dependent UV-Vis spectra, which is attributed to dipole-induced aggregation, and light absorption arising from an inter­molecular charge-transfer process that decreases in energy as the degree of aggregation increases. The crystals display π-stacking where the dipole moments align anti­parallel. Stacked mol­ecules inter­act with the next stack via hydrogen bonds, which is a state of maximum aggregation. Light absorption by charge transfer can be compared to colored inorganic semiconductors such as orange–red CdS, with a band gap of 2.0–2.5 eV.

A host–guest supra­molecular inclusion complex was obtained from the co-crystallization of A1/A2-bromo­but­oxy-hy­droxy difunctionalized pillar[5]arene (PilButBrOH) with adipo­nitrile (ADN), C47H53.18Br0.82O10·C6H8N2. The adipo­nitrile guest is stabilized within the electron-rich cavity of the pillar[5]arene host via multiple C—H⋯O and C—H⋯π inter­actions. Both functional groups on the macrocyclic rim are engaged in supra­molecular inter­actions with an adjacent inclusion complex via hydrogen-bonding (O—H⋯N or C—H⋯Br) inter­actions, resulting in the formation of a supra­molecular dimer in the crystal structure.

Lopinavir is a potent protease inhibitor that is used as a first-line pharmaceutical drug for the treatment of HIV. The multi-component solvated Lopinavir crystal, systematic name (2S)-N-[(2S,4S,5S)-5-[2-(2,6-di­methyl­phen­oxy)acetamido]-4-hy­droxy-1,6-di­phenyl­hexan-2-yl]-3-methyl-2-(2-oxo-1,3-diazinan-1-yl)butanamide–ethane-1,2-diol–water (8/3/7) 8C37H48N4O5·3C2H6O2·7H2O, was prepared using evaporative methods. The crystalline material obtained from this experimental synthesis was characterized and elucidated by single-crystal X-ray diffraction (SC-XRD). The crystal structure is unusual in that the unit cell contains 18 mol­ecules. The stoichiometric ratio of this crystal is eight Lopinavir mol­ecules [8(C37H48N4O5)], three ethane-1,2-diol mol­ecules [3(C2H6O2)] and seven water mol­ecules [7(H2O)]. The crystal packing features both bi- and trifurcated hydrogen bonds between atoms.

Two new zinc(II) complexes, tri­ethyl­ammonium di­chlorido­[2-(4-nitro­phen­yl)-4-phenyl­quinolin-8-olato]zinc(II), (C6H16N){Zn(C21H13N2O3)Cl2] (ZnOQ), and bis­(tri­ethyl­ammonium) {2,2'-[1,4-phenyl­enebis(nitrilo­methyl­idyne)]diphenolato}bis­[di­chlorido­zinc(II)], (C6H16N)2[Zn2(C20H14N2O2)Cl4] (ZnBS), were synthesized and their structures were determined using ESI–MS spectrometry, 1H NMR spectroscopy, and single-crystal X-ray diffraction. The results showed that the ligands 2-(4-nitro­phen­yl)-4-phenyl­quinolin-8-ol (HOQ) and N,N'-bis­(2-hy­droxy­benzyl­idene)benzene-1,4-di­amine (H2BS) were deprotonated by tri­ethyl-amine, forming the counter-ion Et3NH+, which inter­acts via an N—H⋯O hydrogen bond with the ligand. The ZnII atoms have a distorted trigonal–pyramidal (ZnOQ) and distorted tetra­hedral (ZnBS) geometries with a coord­ination number of four, coordinating with the ligands via N and O atoms. The N atoms coordinating with ZnII correspond to the heterocyclic nitro­gen for the HOQ ligand, while for the H2BS ligand, it is the nitro­gen of the imine (CH=N). The crystal packing of ZnOQ is characterized by C—H⋯π inter­actions, while that of ZnBS by C—H⋯Cl inter­actions. The emission spectra showed that ZnBS complex exhibits green fluorescence in the solid state with a small band-gap energy, and the ZnOQ complex does exhibit non-fluorescence.

The major principles and requirements of asymmetric and inclined double-crystal monochromators are re-examined and presented to guide their design and development for significantly reducing heat load density and gradient on the monochromators of fourth-generation synchrotron light sources and X-ray free-electron lasers.

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.

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.

we introduce a novel approach for a real-time dual-frequency feedback system, which has been firstly used at the hard X-ray nanoprobe beamline of SSRF. The BiBEST can then efficiently stabilize X-ray beam position and stability in parallel, making use of different optical systems in the beamline.

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.

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.

Characterization of a material structure with pair distribution function (PDF) analysis typically involves refining a structure model against an experimental data set, but finding or constructing a suitable atomic model for PDF modelling can be an extremely labour-intensive task, requiring carefully browsing through large numbers of possible models. Presented here is POMFinder, a machine learning (ML) classifier that rapidly screens a database of structures, here polyoxometallate (POM) clusters, to identify candidate structures for PDF data modelling. The approach is shown to identify suitable POMs from experimental data, including in situ data collected with fast acquisition times. This automated approach has significant potential for identifying suitable models for structure refinement to extract quantitative structural parameters in materials chemistry research. POMFinder is open source and user friendly, making it accessible to those without prior ML knowledge. It is also demonstrated that POMFinder offers a promising modelling framework for combined modelling of multiple scattering techniques.

X-ray absorption spectroscopy (XAS) is a promising technique for determining structural information from sensitive biological samples, but high-accuracy X-ray absorption fine structure (XAFS) requires corrections of systematic errors in experimental data. Low-temperature XAS and room-temperature X-ray absorption spectro-electrochemical (XAS-EC) measurements of N-truncated amyloid-β samples were collected and corrected for systematic effects such as dead time, detector efficiencies, monochromator glitches, self-absorption, radiation damage and noise at higher wavenumber (k). A new protocol was developed using extended X-ray absorption fine structure (EXAFS) data analysis for monitoring radiation damage in real time and post-analysis. The reliability of the structural determinations and consistency were validated using the XAS measurement experimental uncertainty. The correction of detector pixel efficiencies improved the fitting χ2 by 12%. An improvement of about 2.5% of the structural fitting was obtained after dead-time corrections. Normalization allowed the elimination of 90% of the monochromator glitches. The remaining glitches were manually removed. The dispersion of spectra due to self-absorption was corrected. Standard errors of experimental measurements were propagated from pointwise variance of the spectra after systematic corrections. Calculated uncertainties were used in structural refinements for obtaining precise and reliable values of structural parameters including atomic bond lengths and thermal parameters. This has permitted hypothesis testing.

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

A systematic procedure is introduced for modeling charge-neutral non-polar surfaces of ionic minerals containing polyatomic anions. By integrating distance- and charge-based clustering to identify chemical species within the mineral bulk, our pipeline, PolyCleaver, renders a variety of theoretically viable surface terminations. As a demonstrative example, this approach was applied to forsterite (Mg2SiO4), unveiling a rich interface landscape based on interactions with formaldehyde, a relevant multifaceted molecule, and more particularly in prebiotic chemistry. This high-throughput method, going beyond techniques traditionally applied in the modeling of minerals, offers new insights into the potential catalytic properties of diverse surfaces, enabling a broader exploration of synthetic pathways in complex mineral systems.

DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with a range of customizable convolutional neural network (CNN) architectures for a wide variety of tasks in image analysis to be used in downstream data processing. DLSIA features easy-to-use architectures, such as autoencoders, tunable U-Nets and parameter-lean mixed-scale dense networks (MSDNets). Additionally, this article introduces sparse mixed-scale networks (SMSNets), generated using random graphs, sparse connections and dilated convolutions connecting different length scales. For verification, several DLSIA-instantiated networks and training scripts are employed in multiple applications, including inpainting for X-ray scattering data using U-Nets and MSDNets, segmenting 3D fibers in X-ray tomographic reconstructions of concrete using an ensemble of SMSNets, and leveraging autoencoder latent spaces for data compression and clustering. As experimental data continue to grow in scale and complexity, DLSIA provides accessible CNN construction and abstracts CNN complexities, allowing scientists to tailor their machine learning approaches, accelerate discoveries, foster interdisciplinary collaboration and advance research in scientific image analysis.

Serial crystallography experiments at synchrotron and X-ray free-electron laser (XFEL) sources are producing crystallographic data sets of ever-increasing volume. While these experiments have large data sets and high-frame-rate detectors (around 3520 frames per second), only a small percentage of the data are useful for downstream analysis. Thus, an efficient and real-time data classification pipeline is essential to differentiate reliably between useful and non-useful images, typically known as `hit' and `miss', respectively, and keep only hit images on disk for further analysis such as peak finding and indexing. While feature-point extraction is a key component of modern approaches to image classification, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. This paper proposes a pipeline to categorize the data, consisting of a real-time feature extraction algorithm called modified and parallelized FAST (MP-FAST), an image descriptor and a machine learning classifier. For parallelizing the primary operations of the proposed pipeline, central processing units, graphics processing units and field-programmable gate arrays are implemented and their performances compared. Finally, MP-FAST-based image classification is evaluated using a multi-layer perceptron on various data sets, including both synthetic and experimental data. This approach demonstrates superior performance compared with other feature extractors and classifiers.

This work presents observations of symmetry breakages in the intensity distributions of near-zone-axis convergent-beam electron diffraction (CBED) patterns that can only be explained by the symmetry of the specimen and not the symmetry of the unit cell describing the atomic structure of the material. The specimen is an aluminium–copper–tin alloy containing voids many tens of nanometres in size within continuous single crystals of the aluminium host matrix. Several CBED patterns where the incident beam enters and exits parallel void facets without the incident beam being perpendicular to these facets are examined. The symmetries in their intensity distributions are explained by the specimen morphology alone using a geometric argument based on the multislice theory. This work shows that it is possible to deduce nanoscale morphological information about the specimen in the direction of the electron beam – the elusive third dimension in transmission electron microscopy – from the inspection of CBED patterns.

In antiquity, Pb was a common element added in the production of large bronze artifacts, especially large statues, to impart fluidity to the casting process. As Pb does not form a solid solution with pure Cu or with the Sn–Cu alloy phases, it is normally observed in the metal matrix as globular droplets embedded within or in interstitial positions among the crystals of Sn-bronze (normally the α phase) as the last crystallizing phase during the cooling process of the Cu–Sn–Pb ternary melt. The disequilibrium Sn content of the Pb droplets has recently been suggested as a viable parameter to detect modern materials [Shilstein, Berner, Feldman, Shalev & Rosenberg (2019). STAR Sci. Tech. Archaeol. Res. 5, 29–35]. The application assumes a time-dependent process, with a timescale of hundreds of years, estimated on the basis of the diffusion coefficient of Sn in Pb over a length of a few micrometres [Oberschmidt, Kim & Gupta (1982). J. Appl. Phys. 53, 5672–5677]. Therefore, Pb inclusions in recent Sn-bronze artifacts are actually a metastable solid solution of Pb–Sn containing ∼3% atomic Sn. In contrast, in ancient artifacts, unmixing processes and diffusion of Sn from the micro- and nano-inclusions of Pb to the matrix occur, resulting in the Pb inclusions containing a substantially lower or negligible amount of Sn. The Sn content in the Pb inclusions relies on accurate measurement of the lattice parameter of the phase in the Pb–Sn solid solution, since for low Sn values it closely follows Vegard's law. Here, several new measurements on modern and ancient samples are presented and discussed in order to verify the applicability of the method to the detection of modern artwork pretending to be ancient.

BL19U1, an energy-tunable protein complex crystallography beamline at the Shanghai Synchrotron Radiation Facility, has emerged as one of the most productive MX beamlines since opening to the public in July 2015. As of October 2023, it has contributed to over 2000 protein structures deposited in the Protein Data Bank (PDB), resulting in the publication of more than 1000 scientific papers. In response to increasing interest in structure-based drug design utilizing X-ray crystallography for fragment library screening, enhancements have been implemented in both hardware and data collection systems on the beamline to optimize efficiency. Hardware upgrades include the transition from MD2 to MD2S for the diffractometer, alongside the installation of a humidity controller featuring a rapid nozzle exchanger. This allows users to opt for either low-temperature or room-temperature data collection modes. The control system has been upgraded from Blu-Ice to MXCuBE3, which supports website-mode data collection, providing enhanced compatibility and easy expansion with new features. An automated data processing pipeline has also been developed to offer users real-time feedback on data quality.

Macromolecular crystallography contributes significantly to understanding diseases and, more importantly, how to treat them by providing atomic resolution 3D structures of proteins. This is achieved by collecting X-ray diffraction images of protein crystals from important biological pathways. Spotfinders are used to detect the presence of crystals with usable data, and the spots from such crystals are the primary data used to solve the relevant structures. Having fast and accurate spot finding is essential, but recent advances in synchrotron beamlines used to generate X-ray diffraction images have brought us to the limits of what the best existing spotfinders can do. This bottleneck must be removed so spotfinder software can keep pace with the X-ray beamline hardware improvements and be able to see the weak or diffuse spots required to solve the most challenging problems encountered when working with diffraction images. In this paper, we first present Bragg Spot Detection (BSD), a large benchmark Bragg spot image dataset that contains 304 images with more than 66 000 spots. We then discuss the open source extensible U-Net-based spotfinder Bragg Spot Finder (BSF), with image pre-processing, a U-Net segmentation backbone, and post-processing that includes artifact removal and watershed segmentation. Finally, we perform experiments on the BSD benchmark and obtain results that are (in terms of accuracy) comparable to or better than those obtained with two popular spotfinder software packages (Dozor and DIALS), demonstrating that this is an appropriate framework to support future extensions and improvements.

Presented and discussed here is the implementation of a software solution that provides prompt X-ray diffraction data analysis during fast dynamic compression experiments conducted within the dynamic diamond anvil cell technique. It includes efficient data collection, streaming of data and metadata to a high-performance cluster (HPC), fast azimuthal data integration on the cluster, and tools for controlling the data processing steps and visualizing the data using the DIOPTAS software package. This data processing pipeline is invaluable for a great number of studies. The potential of the pipeline is illustrated with two examples of data collected on ammonia–water mixtures and multiphase mineral assemblies under high pressure. The pipeline is designed to be generic in nature and could be readily adapted to provide rapid feedback for many other X-ray diffraction techniques, e.g. large-volume press studies, in situ stress/strain studies, phase transformation studies, chemical reactions studied with high-resolution diffraction etc.