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.

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.

Our study compares short-range order parameters refined from the diffuse scattering in single-crystal X-ray and single-crystal electron diffraction data. Nb0.84CoSb was chosen as a reference material. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms were refined from the diffuse scattering using a Monte Carlo refinement in DISCUS. The difference between the Sb and Co displacements refined from the diffuse scattering and the Sb and Co displacements refined from the Bragg reflections in single-crystal X-ray diffraction data is 0.012 (7) Å for the refinement on diffuse scattering in single-crystal X-ray diffraction data and 0.03 (2) Å for the refinement on the diffuse scattering in single-crystal electron diffraction data. As electron diffraction requires much smaller crystals than X-ray diffraction, this opens up the possibility of refining short-range order parameters in many technologically relevant materials for which no crystals large enough for single-crystal X-ray diffraction are available.

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.

Bacterial ABC toxin complexes (Tcs) comprise three core proteins: TcA, TcB and TcC. The TcA protein forms a pentameric assembly that attaches to the surface of target cells and penetrates the cell membrane. The TcB and TcC proteins assemble as a heterodimeric TcB–TcC subcomplex that makes a hollow shell. This TcB–TcC subcomplex self-cleaves and encapsulates within the shell a cytotoxic `cargo' encoded by the C-terminal region of the TcC protein. Here, we describe the structure of a previously uncharacterized TcC protein from Yersinia entomophaga, encoded by a gene at a distant genomic location from the genes encoding the rest of the toxin complex, in complex with the TcB protein. When encapsulated within the TcB–TcC shell, the C-terminal toxin adopts an unfolded and disordered state, with limited areas of local order stabilized by the chaperone-like inner surface of the shell. We also determined the structure of the toxin cargo alone and show that when not encapsulated within the shell, it adopts an ADP-ribosyltransferase fold most similar to the catalytic domain of the SpvB toxin from Salmonella typhimurium. Our structural analysis points to a likely mechanism whereby the toxin acts directly on actin, modifying it in a way that prevents normal polymerization.

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

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.

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

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.

Traditional X-ray methods are extensively applied to commercial cement samples in order to determine their physical and chemical properties. Powder patterns are routinely used to quantify the composition of these phase mixtures, but structure determination becomes difficult because of reflection overlapping caused by the high number of different crystal structures. The fast-growing 3D electron diffraction technique and its related automated acquisition protocols arise as a potentially very interesting tool for the cement industry, since they enable the fast and systematic acquisition of diffraction data from individual particles. In this context, electron diffraction has been used in the investigation of the different crystalline phases present in various commercial clinkers for cement. Automated data collection procedures and subsequent data processing have enabled the structural characterization of the different crystal structures from which the α'H polymorph of Ca2SiO4 (belite) exhibited satellite reflections. Its average crystal structure has been known since 1971 and satellite reflections have been reported previously, yet the modulation was never fully described by means of the superspace formalism. Here, the incommensurately modulated structure is solved and refined using harmonic and crenel functions in the superspace group Pnma(α00)0ss, showing the potential of 3D electron diffraction for systematic crystallographic characterizations of cement. A full description of the different belite polymorphs is provided considering this modulated structure.

We report the synthesis and structures of two transition-metal complexes involving 2-(2-hy­droxy­phen­yl)benzimidazole (2hpbi – a ligand of inter­est for its photoluminescent applications), with cobalt, namely, bis­[μ-2-(1H-1,3-benzo­diazol-2-yl)phenolato]bis­[ethanol(thio­cyanato)­cobalt(II)], [Co2(C13H9N2O)2(NCS)2(C2H6O)2], (1), and manganese, namely, bis­[μ-2-(1H-1,3-benzo­diazol-2-yl)phenolato]bis­{[2-(1H-1,3-benzo­diazol-2-yl)phenolato](thio­cyanato)­mang­an­ese(III)} dihydrate, [Mn2(C13H9N2O)4(NCS)2]·2H2O, (2). These structures are two recent examples of a fruitful collaboration between researchers at the Laboratoire de Chimie de Coordination Organique/Organic Coordination Chemistry Laboratory (LCCO), University of Dakar, Senegal and the National Crystallography Service (NCS), School of Chemistry, University Southampton, UK. This productive partnership was forged through meeting at Pan-African Conferences on Crystallography and quickly grew as the plans for the AfCA (African Crystallographic Association) developed. This article therefore also showcases this productive partnership, in celebration of the IUCr's 75 year anniversary and the recent inclusion of AfCA as a Regional Associate of the IUCr.

The structures of 16 phosphane chalcogenide complexes of gold(I) halides, with the general formula R13-nR2nPEAuX (R1 = t-butyl; R2 = isopropyl; n = 0 to 3; E = S or Se; X = Cl, Br or I), are presented. The eight possible chlorido derivatives are: 1a, n = 3, E = S; 2a, n = 2, E = S; 3a, n = 1, E = S; 4a, n = 0, E = S; 5a, n = 3, E = Se; 6a, n = 2, E = Se; 7a, n = 1, E = Se; and 8a, n = 0, E = Se, and the corresponding bromido derivatives are 1b–8b in the same order. However, 2a and 2b were badly disordered and 8a was not obtained. The iodido derivatives are 2c, 6c and 7c (numbered as for the series a and b). All structures are solvent-free and all have Z' = 1 except for 6b and 6c (Z' = 2). All mol­ecules show the expected linear geometry at gold and approximately tetra­hedral angles P—E—Au. The presence of bulky ligands forces some short intra­molecular contacts, in particular H⋯Au and H⋯E. The Au—E bond lengths have a slight but consistent tendency to be longer when trans to a softer X ligand, and vice versa. The five compounds 1a, 5a, 6a, 1b and 5b form an isotypic set, despite the different alkyl groups in 6a. Compounds 3a/3b, 4b/8b and 6b/6c form isotypic pairs. The crystal packing can be analysed in terms of various types of secondary inter­actions, of which the most frequent are `weak' hydrogen bonds from methine hydrogen atoms to the halogenido ligands. For the structure type 1a, H⋯X and H⋯E contacts combine to form a layer structure. For 3a/3b, the packing is almost featureless, but can be described in terms of a double-layer structure involving borderline H⋯Cl/Br and H⋯S contacts. In 4a and 4b/8b, which lack methine groups, Cmeth­yl—H⋯X contacts combine to form layer structures. In 7a/7b, short C—H⋯X inter­actions form chains of mol­ecules that are further linked by association of short Au⋯Se contacts to form a layer structure. The packing of compound 6b/6c can conveniently be analysed for each independent mol­ecule separately, because they occupy different regions of the cell. Mol­ecule 1 forms chains in which the mol­ecules are linked by a Cmethine⋯Au contact. The mol­ecules 2 associate via a short Se⋯Se contact and a short H⋯X contact to form a layer structure. The packing of compound 2c can be described in terms of two short Cmethine—H⋯I contacts, which combine to form a corrugated ribbon structure. Compound 7c is the only compound in this paper to feature Au⋯Au contacts, which lead to twofold-symmetric dimers. Apart from this, the packing is almost featureless, consisting of layers with only translation symmetry except for two very borderline Au⋯H contacts.

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 reaction between 2-pyridyl­selenenyl chloride and isobutyro­nitrile results in the formation of the corresponding cationic pyridinium-fused 1,2,4-seleno­diazole, namely, 3-(propan-2-yl)-1,2,4-[1,2,4]selena­diazolo[4,5-a]pyridin-4-ylium chloride, C9H11N2Se+·Cl−, in high yield (89%). The structure of the compound, established by means of single-crystal X-ray analysis at 100 K, has monoclinic (P21/c) symmetry and revealed the presence of bifurcated chalcogen-hydrogen bonding Se⋯Cl−⋯H—Cl, and these non-covalent contacts were analysed by DFT calculations followed by a topological analysis of the electron-density distribution (ωB97XD/6-311++G** level of theory).

The structures of fourteen halochalcogenyl­phospho­nium tetra­halogen­ido­aurates(III), phosphane chalcogenide derivatives with general formula [R13–nR2nPEX][AuX4] (R1 = t-butyl; R2 = isopropyl; n = 0 to 3; E = S or Se; X = Cl or Br) are presented. The eight possible chlorido derivatives are: 17a, n = 3, E = S; 18a, n = 2, E = S; 19a, n = 1, E = S; 20a, n = 0, E = S; 21a, n = 3, E = Se; 22a, n = 2, E = Se; 23a, n = 1, E = Se; and 24a, n = 0, E = Se, and the corresponding bromido derivatives are 17b–24b in the same order. Structures were obtained for all compounds except for the tri-t-butyl derivatives 24a and 24b. Isotypy is observed for 18a/18b/22a/22b, 19a/23a, 17b/21b and 19b/23b. In eleven of the compounds, X⋯X contacts (mostly very short) are observed between the cation and anion, whereby the E—X⋯X groups are approximately linear and the X⋯X—Au angles approximately 90°. The exceptions are 17a, 19a and 23a, which instead display short E⋯X contacts. Bond lengths in the cations correspond to single bonds P—E and E—X. For each group with constant E and X, the P—E—X bond-angle values increase monotonically with the steric bulk of the alkyl groups. The packing is analysed in terms of E⋯X, X⋯X (some between anions alone), H⋯X and H⋯Au contacts. Even for isotypic compounds, some significant differences can be discerned.

The reaction of lithium hexa­methyl­disilyl­amide, [Li{N(Si(CH3)3)2}] (LiHMDS), with 4,4-dimethyl-2-phenyl-2-oxazoline (Phox, C11H13NO) in hexane produced colourless crystals of bis­(4,4-dimethyl-2-phenyl-2-oxazoline-κN)(hexa­methyl­disilyl­amido-κN)lithium, [Li(C6H18NSi2)(C11H13NO)2] or [Li{N(Si(CH3)3)2}(Phox)2] in high yield (89%). Despite the 1:1 proportion of the starting materials in the reaction mixture, the product formed with a 1:2 amide:oxazoline ratio. In the unit cell of the C2/c space group, the neutral mol­ecules lie on twofold rotation axes coinciding with the Li—N(amide) bonds. The lithium(I) centre adopts a trigonal–planar coordination geometry with three nitro­gen donor atoms, one from the HMDS anion and two from the oxazolines. All ligands are monodentate. In the phenyl­oxazoline units, the dihedral angle defined by the five-membered heterocyclic rings is 35.81 (5)°, while the phenyl substituents are approximately face-to-face, separated by 3.908 (5) Å. In the amide, the methyl groups assume a nearly eclipsed arrangement to minimize steric repulsion with the analogous substituents on the oxazoline rings. The non-covalent inter­actions in the solid-state structure of [Li{N(Si(CH3)3)2}(Phox)2] were assessed by Hirshfeld surface analysis and fingerprint plots. This new compound is attractive for catalysis due to its unique structural features.

Coarse colorless single crystals of lithium lutetium bis­[orthomolybdate(VI)], LiLu[MoO4]2, were obtained as a by-product from a reaction aimed at lithium derivatives of lutetium molybdate. The title compound crystallizes in the scheelite structure type (tetra­gonal, space group I41/a) with two formula units per unit cell. The Wyckoff position 4b (site symmetry overline{4}) comprises a mixed occupancy of Li+ and Lu3+ cations in a 1:1 ratio. In comparison with a previous powder X-ray study [Cheng et al. (2015). Dalton Trans. 44, 18078–18089.] all atoms were refined with anisotropic displacement parameters.

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 structural characterization is reported of the supra­molecular complex between the tetra­quinoxaline-based cavitand 2,8,14,20-tetra­hexyl-6,10:12,16:18,22:24,4-O,O'-tetra­kis­(quinoxaline-2,3-di­yl)calix[4]resorcinarene (QxCav) with benzo­nitrile. The complex, of general formula C84H80N8O8·2C7H5N, crystallizes in the space group Poverline{1} with two independent mol­ecules in the asymmetric unit, displaying very similar geometrical parameters. For each complex, one of the benzo­nitrile mol­ecules is engulfed inside the cavity, while the other is located among the alkyl legs at the lower rim. The host and the guests mainly inter­act through weak C—H⋯π, C—H⋯N and dispersion inter­actions. These inter­actions help to consolidate the formation of supra­molecular chains running along the crystallographic b-axis direction.

Three new 1H-indole derivatives, namely, 2-(bromo­meth­yl)-3-methyl-1-(phenyl­sulfon­yl)-1H-indole, C16H14BrNO2S, (I), 2-[(E)-2-(2-bromo-5-meth­oxy­phen­yl)ethen­yl]-3-methyl-1-(phenyl­sulfon­yl)-1H-indole, C24H20BrNO3S, (II), and 2-[(E)-2-(2-bromo­phen­yl)ethen­yl]-3-methyl-1-(phenyl­sulfon­yl)-1H-indole, C23H18BrNO2S, (III), exhibit nearly orthogonal orientations of their indole ring systems and sulfonyl-bound phenyl rings. Such conformations are favourable for inter­molecular bonding involving sets of slipped π–π inter­actions between the indole systems and mutual C—H⋯π hydrogen bonds, with the generation of two-dimensional monoperiodic patterns. The latter are found in all three structures, in the form of supra­molecular columns with every pair of successive mol­ecules related by inversion. The crystal packing of the compounds is additionally stabilized by weaker slipped π–π inter­actions between the outer phenyl rings (in II and III) and by weak C—H⋯O, C—H⋯Br and C—H⋯π hydrogen bonds. The structural significance of the different kinds of inter­actions agree with the results of a Hirshfeld surface analysis and the calculated inter­action energies. In particular, the largest inter­action energies (up to −60.8 kJ mol−1) are associated with pairing of anti­parallel indole systems, while the energetics of weak hydrogen bonds and phenyl π–π inter­actions are comparable and account for 13–34 kJ mol−1.

The crystal structure of the title 2:1 mol­ecular complex between 2-(allyl­thio)­pyridine and 1,2,4,5-tetra­fluoro-3,6-di­iodo­benzene, C6F4I2·2C8H9NS, at 100 K has been determined in the monoclinic space group P21/c. The most noteworthy characteristic of the complex is the halogen bond between iodine and the pyridine ring with a short N⋯I contact [2.8628 (12) Å]. The Hirshfeld surface analysis shows that the hydrogen⋯hydrogen contacts dominate the crystal packing with a contribution of 32.1%.

The cyclic peptide cyclo(Val-Leu-Leu-d-Phe-Pro)2 (peptide 1) was specifically designed for structural chemistry investigations, drawing inspiration from Gramicidin S (GS). Previous studies have shown that Pro residues within 1 adopt a down-puckering conformation of the pyrrolidine ring. By incorporating fluoride-Pro with 4-trans/cis-isomers into 1, an up-puckering conformation was successfully induced. In the current investigation, introducing hy­droxy­prolines with 4-trans/cis-isomer configurations (tHyp/cHyp) into 1 gave cyclo(Val-Leu-Leu-d-Phe-tHyp)2 methanol disolvate monohydrate, C62H94N10O12·2CH4O·H2O (4), and cyclo(Val-Leu-Leu-d-Phe-cHyp)2 monohydrate, C62H94N10O12·H2O (5), respectively. However, the puckering of 4 and 5 remained in the down conformation, regardless of the geometric position of the hydroxyl group. Although the backbone structure of 4 with trans-substitution was asymmetric, the asymmetric backbone of 5 with cis-substitution was unexpected. It is speculated that the anti­cipated influence of stress from the geometric positioning, which was expected to affect the puckering, may have been mitigated by inter­actions between the hydroxyl groups of hy­droxy­proline, the solvent mol­ecules, and peptides.

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.

A new pyridine-fused seleno­diazo­lium salt, 3-(phenyl­selan­yl)[1,2,4]selena­diazolo[4,5-a]pyridin-4-ylium chloride di­chloro­methane 0.352-solvate, C12H9N2Se2+·Cl−·0.352CH2Cl2, was obtained from the reaction between 2-pyridyl­selenenyl chloride and phenyl­seleno­cyanate. Single-crystal structural analysis revealed the presence of C—H⋯N, C—H⋯Cl−, C—H⋯Se hydrogen bonds as well as chalcogen–chalcogen (Se⋯Se) and chalcogen–halogen (Se⋯Cl−) inter­actions. Non-covalent inter­actions were explored by DFT calculations followed by topological analysis of the electron density distribution (QTAIM analysis). The structure consists of pairs of seleno­diazo­lium moieties arranged in a head-to-tail fashion surrounding disordered di­chloro­methane mol­ecules. The assemblies are connected by C—H⋯Cl− and C—H⋯N hydrogen bonds, forming layers, which stack along the c-axis direction connected by bifurcated Se⋯Cl−⋯H—C inter­actions.

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.

Low-energy electron diffraction patterns contain precise information about the structure of the surface studied. However, retrieving the real space lattice periodicity from complex diffraction patterns is challenging, especially when the modeled patterns originate from superlattices with large unit cells composed of several symmetry-equivalent domains without a simple relation to the substrate. This work presents ProLEED Studio software, built to provide simple, intuitive and precise modeling of low-energy electron diffraction patterns. The interactive graphical user interface allows real-time modeling of experimental diffraction patterns, change of depicted diffraction spot intensities, visualization of different diffraction domains, and manipulation of any lattice points or diffraction spots. The visualization of unit cells, lattice vectors, grids and scale bars as well as the possibility of exporting ready-to-publish models in bitmap and vector formats significantly simplifies the modeling process and publishing of results.

BioXTAS RAW is a free open-source program for reduction, analysis and modelling of biological small-angle scattering data. Here, the new developments in RAW version 2 are described. These include improved data reduction using pyFAI; updated automated Guinier fitting and Dmax finding algorithms; automated series (e.g. size-exclusion chromatography coupled small-angle X-ray scattering or SEC-SAXS) buffer- and sample-region finding algorithms; linear and integral baseline correction for series; deconvolution of series data using regularized alternating least squares (REGALS); creation of electron-density reconstructions using electron density via solution scattering (DENSS); a comparison window showing residuals, ratios and statistical comparisons between profiles; and generation of PDF reports with summary plots and tables for all analysis. Furthermore, there is now a RAW API, which can be used without the graphical user interface (GUI), providing full access to all of the functionality found in the GUI. In addition to these new capabilities, RAW has undergone significant technical updates, such as adding Python 3 compatibility, and has entirely new documentation available both online and in the program.

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.

A deep-learning algorithm is proposed for the inpainting of Bragg coherent diffraction imaging (BCDI) patterns affected by detector gaps. These regions of missing intensity can compromise the accuracy of reconstruction algorithms, inducing artefacts in the final result. It is thus desirable to restore the intensity in these regions in order to ensure more reliable reconstructions. The key aspect of the method lies in the choice of training the neural network with cropped sections of diffraction data and subsequently patching the predictions generated by the model along the gap, thus completing the full diffraction peak. This approach enables access to a greater amount of experimental data for training and offers the ability to average overlapping sections during patching. As a result, it produces robust and dependable predictions for experimental data arrays of any size. It is shown that the method is able to remove gap-induced artefacts on the reconstructed objects for both simulated and experimental data, which becomes essential in the case of high-resolution BCDI experiments.

Ptychography is a powerful computational imaging technique with microscopic imaging capability and adaptability to various specimens. To obtain an imaging result, it requires a phase-retrieval algorithm whose performance directly determines the imaging quality. Recently, deep neural network (DNN)-based phase retrieval has been proposed to improve the imaging quality from the ordinary model-based iterative algorithms. However, the DNN-based methods have some limitations because of the sensitivity to changes in experimental conditions and the difficulty of collecting enough measured specimen images for training the DNN. To overcome these limitations, a ptychographic phase-retrieval algorithm that combines model-based and DNN-based approaches is proposed. This method exploits a DNN-based denoiser to assist an iterative algorithm like ePIE in finding better reconstruction images. This combination of DNN and iterative algorithms allows the measurement model to be explicitly incorporated into the DNN-based approach, improving its robustness to changes in experimental conditions. Furthermore, to circumvent the difficulty of collecting the training data, it is proposed that the DNN-based denoiser be trained without using actual measured specimen images but using a formula-driven supervised approach that systemically generates synthetic images. In experiments using simulation based on a hard X-ray ptychographic measurement system, the imaging capability of the proposed method was evaluated by comparing it with ePIE and rPIE. These results demonstrated that the proposed method was able to reconstruct higher-spatial-resolution images with half the number of iterations required by ePIE and rPIE, even for data with low illumination intensity. Also, the proposed method was shown to be robust to its hyperparameters. In addition, the proposed method was applied to ptychographic datasets of a Simens star chart and ink toner particles measured at SPring-8 BL24XU, which confirmed that it can successfully reconstruct images from measurement scans with a lower overlap ratio of the illumination regions than is required by ePIE and rPIE.

Online courses and innovative teaching methods have triggered a trend in education, where the integration of multimedia, online resources and interactive tools is reshaping the view of both virtual and traditional classrooms. The use of interactive tools extends beyond the boundaries of the physical classroom, offering students the flexibility to access materials at their own speed and convenience and enhancing their learning experience. In the field of crystallography, there are a wide variety of free online resources such as web pages, interactive applets, databases and programs that can be implemented in fundamental crystallography courses for different academic levels and curricula. This paper discusses a variety of resources that can be helpful for crystallographic symmetry handling and visualization, discussing four specific resources in detail: the Bilbao Crystallographic Server, the Cambridge Structural Database, VESTA and Jmol. The utility of these resources is explained and shown by several illustrative examples.

Slow-cooled CF8M duplex stainless steel is used for critical parts of the primary coolant pipes of nuclear reactors. This steel can endure severe service conditions, but it tends to become more brittle upon very long-term aging (tens of years). Therefore, it is essential to understand its specific microstructure and temporal evolution. As revealed by electron backscatter diffraction (EBSD) analyses, the microstructure consists of millimetre-scale ferritic grains within which austenite lath packets have grown with preferred crystallographic orientations concerning the parent ferritic phase far from the ferrite grain boundaries. In these lath packets where the austenite phase is nucleated, the lath morphology and crystal orientation accommodate the two ferrite orientations. Globally, the Pitsch orientation relationship appears to display the best agreement with the experimental data compared with other classical relationships. The austenite lath packets are parallel plate-shaped laths, characterized by their normal n. A novel methodology is introduced to elucidate the expected relationship between n and the crystallographic orientation given the coarse interfaces, even though n is only partly known from the observation surface, in contrast to the 3D crystal orientations measured by EBSD. The distribution of retrieved normals n is shown to be concentrated over a set of discrete orientations. Assuming that the ferrite and austenite obey the Pitsch orientation relationship, the determined lath normals are close to an invariant direction of the parent phase given by the same orientation relationship.

SPring-8-II is a major upgrade project of SPring-8 that was inaugurated in October 1997 as a third-generation synchrotron radiation light source. This upgrade project aims to achieve three goals simultaneously: achievement of excellent light source performance, refurbishment of aged systems, and significant reduction in power consumption for the entire facility. A small emittance of 50 pm rad will be achieved by (1) replacing the existing double-bend lattice structure with a five-bend achromat one, (2) lowering the stored beam energy from 8 to 6 GeV, (3) increasing the horizontal damping partition number from 1 to 1.3, and (4) enhancing horizontal radiation damping by installing damping wigglers in long straight sections. The use of short-period in-vacuum undulators allows ultrabrilliant X-rays to be provided while keeping a high-energy spectral range even at the reduced electron-beam energy of 6 GeV. To reduce power consumption, the dedicated, aged injector system has been shut down and the high-performance linear accelerator of SACLA, a compact X-ray free-electron laser (XFEL) facility, is used as the injector of the ring in a time-shared manner. This allows the simultaneous operation of XFEL experiments at SACLA and full/top-up injection of the electron beam into the ring. This paper overviews the concept of the SPring-8-II project, the system design of the light source and the details of the accelerator component design.

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