BGS to update geological maps of Strathmore  British Geological Survey

The crystal structure of a neo­pentyl­oxypillar[5]arene with two pyridine mol­ecules encapsulated in the macrocyclic cavity is reported.

(Time-resolved) macromolecular crystallography at the new ESRF-ID29 beamline is described.

Crystal structure and topology of two new thiosulfates formed with mono- and diprotonated species of 1-methylpiperazine is reported.

The crystal structure of calcium atorvastatin trihydrate was redetermined from previously published synchrotron powder diffraction data to give a much-improved agreement with two independent density-functional theory calculations.

1,2-Bis(3,5-di­methyl-2-thienyl)perfluoro­cyclo­pentene formed its own spherulites by sublimation onto the hydro­philic surfaces of the (0001) planes of α-quartz and sapphire substrates. The formation of different morphologies of these spherulites was attributed to the surface properties of each substrate. Depending on the morphology of the spherulites, hollow rod crystals with cross sections of different sizes and shapes and branching structures were generated on the surfaces of the spherulites.

Five multicomponent solid forms of an antifungal drug flucytosine are reported with a hygroscopic stability study. A detailed CSD search on the cocrystal/salts of flucytosine is evaluated and correlated the structures based on bond angles and bond distances.

Sublimation methods utilizing the surface properties of substrates can address the challenge of controlling hollow morphologies in rod crystals. Spherulites were formed on the hydrophilic surface of the (0001) planes of α-quartz and sapphire substrates by sublimation of 1,2-bis(3,5-dimethyl-2-thienyl)perfluorocyclopentene (1a). Various types of hollow morphologies, distinguished by the size and shape of their cross sections and by the presence or absence of branching structures, were formed separately on α-quartz and sapphire substrates. Such precise control of the hollow morphologies was attributed to the wettability of each substrate, leading to the formation of spherulites of 1a. In addition, it was indicated that the formation process of the surface morphologies of spherulites was associated with the hollow morphologies of rod crystals of 1a.

With ever-improving quantum-mechanical computational methods, the accuracy requirements for experimental crystal structures increase. The crystal structure of calcium atorvastatin trihydrate, which has 56 degrees of freedom when determined with a real-space algorithm, was determined from powder diffraction data by Hodge et al. [Powder Diffr. (2020), 35, 136–143]. The crystal structure was a good fit to the experimental data, indicating that the electron density had been captured essentially correctly, but two independent quantum-mechanical calculations disagreed with the experimental structure and with each other. Using the same experimental data, the crystal structure was redetermined from scratch and it was shown that it can be reproduced within a root-mean-square Cartesian displacement of 0.1 Å by two independent quantum-mechanical calculations. The consequences for the calculated energies and solubilities are described.

A novel approach to computationally enhance the sampling of molecular crystal structures is proposed and tested. This method is based on the use of extended variables coupled to a Monte Carlo based crystal polymorph generator. Inspired by the established technique of quasi-random sampling of polymorphs using the rigid molecule constraint, this approach represents molecular clusters as extended variables within a thermal reservoir. Polymorph unit-cell variables are generated using pseudo-random sampling. Within this framework, a harmonic coupling between the extended variables and polymorph configurations is established. The extended variables remain fixed during the inner loop dedicated to polymorph sampling, enforcing a stepwise propagation of the extended variables to maintain system exploration. The final processing step results in a polymorph energy landscape, where the raw structures sampled to create the extended variable trajectory are re-optimized without the thermal coupling term. The foundational principles of this approach are described and its effectiveness using both a Metropolis Monte Carlo type algorithm and modifications that incorporate replica exchange is demonstrated. A comparison is provided with pseudo-random sampling of polymorphs for the molecule coumarin. The choice to test a design of this algorithm as relevant for enhanced sampling of crystal structures was due to the obvious relation between molecular structure variables and corresponding crystal polymorphs as representative of the inherent vapor to crystal transitions that exist in nature. Additionally, it is shown that the trajectories of extended variables can be harnessed to extract fluctuation properties that can lead to valuable insights. A novel thermodynamic variable is introduced: the free energy difference between ensembles of Z' = 1 and Z' = 2 crystal polymorphs.

Parameters in analytical models for X-ray form factors of ions f0(s), based on the inverse Mott–Bethe formula involving a variable number of Gaussians, are determined for a wide range of published data sets {s, f0(s)}. The models reproduce the calculated form-factor values close to what is expected from a uniform statistical distribution with limits determined by their precision. For different ions associated with the same atom, the number of Gaussians in the models decreases with increasing net positive charge.

In electron diffraction, thermal atomic motion produces incoherent scattering over a relatively wide angular range, which appears as a diffuse background that is usually subtracted from measurements of Bragg spot intensities in structure solution methods. The transfer of electron flux from Bragg spots to diffuse scatter is modelled using complex scattering factors f + if' in the Bloch wave methodology. In a two-beam Einstein model the imaginary `absorptive' scattering factor f' can be obtained by the evaluation of an integral containing f over all possible scattering angles. While more sophisticated models of diffuse scatter are widely used in the electron microscopy community, it is argued in this paper that this simple model is appropriate for current structure solution and refinement methods. The two-beam model is a straightforward numerical calculation, but even this simplistic approach can become time consuming for simulations of materials with large numbers of atoms in the unit cell and/or many incident beam orientations. Here, a parameterized form of f' is provided for 103 elements as neutral, spherical atoms that reduces calculation time considerably.

Small-angle X-ray scattering (SAXS) is widely used to analyze the shape and size of nanoparticles in solution. A multitude of models, describing the SAXS intensity resulting from nanoparticles of various shapes, have been developed by the scientific community and are used for data analysis. Choosing the optimal model is a crucial step in data analysis, which can be difficult and time-consuming, especially for non-expert users. An algorithm is proposed, based on machine learning, representation learning and SAXS-specific preprocessing methods, which instantly selects the nanoparticle model best suited to describe SAXS data. The different algorithms compared are trained and evaluated on a simulated database. This database includes 75 000 scattering spectra from nine nanoparticle models, and realistically simulates two distinct device configurations. It will be made freely available to serve as a basis of comparison for future work. Deploying a universal solution for automatic nanoparticle model selection is a challenge made more difficult by the diversity of SAXS instruments and their flexible settings. The poor transferability of classification rules learned on one device configuration to another is highlighted. It is shown that training on several device configurations enables the algorithm to be generalized, without degrading performance compared with configuration-specific training. Finally, the classification algorithm is evaluated on a real data set obtained by performing SAXS experiments on nanoparticles for each of the instrumental configurations, which have been characterized by transmission electron microscopy. This data set, although very limited, allows estimation of the transferability of the classification rules learned on simulated data to real data.

A novel automated high-throughput screening approach, ClusterFinder, is reported for finding candidate structures for atomic pair distribution function (PDF) structural refinements. Finding starting models for PDF refinements is notoriously difficult when the PDF originates from nanoclusters or small nanoparticles. The reported ClusterFinder algorithm can screen 104 to 105 candidate structures from structural databases such as the Inorganic Crystal Structure Database (ICSD) in minutes, using the crystal structures as templates in which it looks for atomic clusters that result in a PDF similar to the target measured PDF. The algorithm returns a rank-ordered list of clusters for further assessment by the user. The algorithm has performed well for simulated and measured PDFs of metal–oxido clusters such as Keggin clusters. This is therefore a powerful approach to finding structural cluster candidates in a modelling campaign for PDFs of nanoparticles and nanoclusters.

A crystal structure with N atoms in its unit cell can be solved starting from a model with atoms 1 to j − 1 being located. To locate the next atom j, the method uses a modified definition of the traditional R1 factor where its dependencies on the locations of atoms j + 1 to N are removed. This modified R1 is called the single-atom R1 (sR1), because the locations of atoms 1 to j − 1 in sR1 are the known parameters, and only the location of atom j is unknown. Finding the correct position of atom j translates thus into the optimization of the sR1 function, with respect to its fractional coordinates, xj, yj, zj. Using experimental data, it has been verified that an sR1 has a hole near each missing atom. Further, it has been verified that an algorithm based on sR1, hereby called the sR1 method, can solve crystal structures (with up to 156 non-hydrogen atoms in the unit cell). The strategy to carry out this calculation has also been optimized. The main feature of the sR1 method is that, starting from a single arbitrarily positioned atom, the structure is gradually revealed. With the user's help to delete poorly determined parts of the structure, the sR1 method can build the model to a high final quality. Thus, sR1 is a viable and useful tool for solving crystal structures.

In Part I of this series, all topologically possible 1-periodic infinite graphs (chain graphs) representing chains of tetrahedra with up to 6–8 vertices (tetrahedra) per repeat unit were generated. This paper examines possible restraints on embedding these chain graphs into Euclidean space such that they are compatible with the metrics of chains of tetrahedra in observed crystal structures. Chain-silicate minerals with T = Si4+ (plus P5+, V5+, As5+, Al3+, Fe3+, B3+, Be2+, Zn2+ and Mg2+) have a grand nearest-neighbour 〈T–T〉 distance of 3.06±0.15 Å and a minimum T⋯T separation of 3.71 Å between non-nearest-neighbour tetrahedra, and in order for embedded chain graphs (called unit-distance graphs) to be possible atomic arrangements in crystals, they must conform to these metrics, a process termed equalization. It is shown that equalization of all acyclic chain graphs is possible in 2D and 3D, and that equalization of most cyclic chain graphs is possible in 3D but not necessarily in 2D. All unique ways in which non-isomorphic vertices may be moved are designated modes of geometric modification. If a mode (m) is applied to an equalized unit-distance graph such that a new geometrically distinct unit-distance graph is produced without changing the lengths of any edges, the mode is designated as valid (mv); if a new geometrically distinct unit-distance graph cannot be produced, the mode is invalid (mi). The parameters mv and mi are used to define ranges of rigidity of the unit-distance graphs, and are related to the edge-to-vertex ratio, e/n, of the parent chain graph. The program GraphT–T was developed to embed any chain graph into Euclidean space subject to the metric restraints on T–T and T⋯T. Embedding a selection of chain graphs with differing e/n ratios shows that the principal reason why many topologically possible chains cannot occur in crystal structures is due to violation of the requirement that T⋯T > 3.71 Å. Such a restraint becomes increasingly restrictive as e/n increases and indicates why chains with stoichiometry TO<2.5 do not occur in crystal structures.

The atomic pair distribution function (PDF) is a real-space representation of the structure of a material. Experimental PDFs are obtained using a Fourier transform from total scattering data which may or may not have Bragg diffraction peaks. The determination of Bragg peak resolution in scattering data from the fundamental physical parameters of the diffractometer used is well established, but after the Fourier transform from reciprocal to direct space, these contributions are harder to identify. Starting from an existing definition of the resolution function of large-area detectors for X-ray diffraction, this approach is expanded into direct space. The effect of instrumental parameters on PDF peak resolution is developed mathematically, then studied with modelling and comparison with experimental PDFs of LaB6 from measurements made in different-sized capillaries.

Sorghum, a short-day tropical plant, has been adapted for temperate grain production, in particular through the selection of variants at the MATURITY loci (Ma1–Ma6) that reduce photoperiod sensitivity. Ma3 encodes phytochrome B (phyB), a red/far-red photochromic biliprotein photoreceptor. The multi-domain gene product, comprising 1178 amino acids, autocatalytically binds the phytochromobilin chromophore to form the photoactive holophytochrome (Sb.phyB). This study describes the development of an efficient heterologous overproduction system which allows the production of large quantities of various holoprotein constructs, along with purification and crystallization procedures. Crystals of the Pr (red-light-absorbing) forms of NPGP, PGP and PG (residues 1–655, 114–655 and 114–458, respectively), each C-terminally tagged with His6, were successfully produced. While NPGP crystals did not diffract, those of PGP and PG diffracted to 6 and 2.1 Å resolution, respectively. Moving the tag to the N-terminus and replacing phytochromobilin with phycocyanobilin as the ligand produced PG crystals that diffracted to 1.8 Å resolution. These results demonstrate that the diffraction quality of challenging protein crystals can be improved by removing flexible regions, shifting fusion tags and altering small-molecule ligands.

Plasmodium vivax is a major cause of malaria, which poses an increased health burden on approximately one third of the world's population due to climate change. Primaquine, the preferred treatment for P. vivax malaria, is contraindicated in individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency, a common genetic cause of hemolytic anemia, that affects ∼2.5% of the world's population and ∼8% of the population in areas of the world where P. vivax malaria is endemic. The Seattle Structural Genomics Center for Infectious Disease (SSGCID) conducted a structure–function analysis of P. vivax N-myristoyltransferase (PvNMT) as part of efforts to develop alternative malaria drugs. PvNMT catalyzes the attachment of myristate to the N-terminal glycine of many proteins, and this critical post-translational modification is required for the survival of P. vivax. The first step is the formation of a PvNMT–myristoyl–CoA binary complex that can bind to peptides. Understanding how inhibitors prevent protein binding will facilitate the development of PvNMT as a viable drug target. NMTs are secreted in all life stages of malarial parasites, making them attractive targets, unlike current antimalarials that are only effective during the plasmodial erythrocytic stages. The 2.3 Å resolution crystal structure of the ternary complex of PvNMT with myristoyl-CoA and a novel inhibitor is reported. One asymmetric unit contains two monomers. The structure reveals notable differences between the PvNMT and human enzymes and similarities to other plasmodial NMTs that can be exploited to develop new antimalarials.

The crystal structure of the intracellular domain of transforming growth factor β type I receptor (TβR1) in complex with the competitive inhibitor SB505124 is presented. The study provides insights into the structure and function of TβR1 in complex with SB505124, and as such offers molecular-level understanding of the inhibition of this critical signalling pathway. The potential of SB505124 as an avenue for therapy in cancer treatment is discussed on basis of the results.

This review summarizes the methodological aspects of laboratory X-ray powder micro-diffraction and demonstrates the assets of the method in the research of painted artworks for evaluation of their provenance or diagnosing their degradation.

The growth quality of AlN single crystals was improved by optimizing the crucible structure for Al vapor transport with the help of finite element simulation.

The correct determination of X-ray transmission at X-ray nanoprobes equipped with small beamstops for small- and wide-angle X-ray scattering collection is an unsolved problem with huge implications for data correction pipelines. We present a cost-effective solution to detect the transmission via the X-ray fluorescence of the beamstop with an avalanche photodiode.

New software capabilities in RMCProfile allow researchers to study the structure of materials by combining machine learning interatomic potentials and reverse Monte Carlo.

A new processing technique for synchrotron scanning 3D X-ray diffraction data is introduced, utilizing symmetric Bragg reflections hkl and hkl, known as Friedel pairs. This technique is designed to tackle the difficulties associated with large, highly deformed, polyphase materials, especially geological samples.

This study examines the quality of charge density obtained by fitting the multipole model to wavefunctions in different basis sets. The complex analysis reveals that changing the basis set quality from double- to triple-zeta can notably improve the charge density related properties of a multipole model.

Here, an open-source Python library for identifying and screening potential stacking fault models in crystalline materials with planar disorder is presented.

The performance of a high-Z photon-counting detector for powder diffraction measurements at high (>50 keV) energies is characterized, and the appropriate corrections are described in order to obtain data of higher quality than have previously been obtained from 2D detectors in these energy ranges.

The L-edge EXAFS of the entire set of lanthanide oxides were collected and modeled, taking into consideration the aggregation of inequivalent absorbing sites, geometric parameterization of the crystal lattice and multielectron excitation removal.

Here we describe TOMOMAN (TOMOgram MANager), an extensible open-sourced software package for handling cryo-electron tomography data preprocessing. TOMOMAN streamlines interoperability between a wide range of external packages and provides tools for project sharing and archival.

This article reports an investigation into the effects of specific radiation damage to halogenated ligands in crystal structures of protein-inhibitor complexes.

In the complex, the ligand binds to the metal through an oxygen atom. The geometry of the seven-coordinate U atom is penta­gonal bipyramidal, with the uranyl O atoms in apical positions.

A chiral nickel(II) Schiff base complex derived from 2-hy­droxy­benzo­phenone and (1S,2S)-1,2-di­phenyl­ethyl­enedi­amine shows a λ conformation of the central di­amine chelate ring. The substituents on the C&z-dbnd;N carbon atoms significantly affect the circular dichroism spectra.

The crystal structure of a metabolite of the insecticide/acaricide etoxazole, designated R13 is presented along with a Hirshfeld surface analysis of inter­molecular inter­actions present in the crystal structure.

N-terminally hexahistidine-tagged O. volvulus macrophage migration inhibitory factor-1 has a unique jellyfish-like structure with the prototypical macrophage migration inhibitory factor trimer as the `head' and a C-terminal extension as the `tail'.

Quantitative X-ray diffraction approaches require careful correction for sample transmission. Though this is a routine task at state-of-the-art small-angle X-ray scattering (SAXS), wide-angle X-ray scattering (WAXS) or diffraction beamlines at synchrotron facilities, the transmission signal cannot be recorded concurrently with SAXS/WAXS when using the small, sub-millimetre beamstops at many X-ray nanoprobes during SAXS/WAXS experiments due to the divergence-limited size of the beamstop and the generally tight geometry. This is detrimental to the data quality and often the only solution is to re-scan the sample with a PIN photodiode as a detector to obtain transmission values. In this manuscript, we present a simple yet effective solution to this problem in the form of a small beamstop with an inlaid metal target for optimal fluorescence yield. This fluorescence can be detected with a high-sensitivity avalanche photodiode and provides a linear counter to determine the sample transmission.

The present study introduces a processing strategy for synchrotron scanning 3D X-ray diffraction (s3DXRD) data, aimed at addressing the challenges posed by large, highly deformed, polyphase materials such as crystalline rocks. Leveraging symmetric Bragg reflections known as Friedel pairs, our method enables diffraction events to be precisely located within the sample volume. This method allows for fitting the phase, crystal structure and unit-cell parameters at the intra-grain scale on a voxel grid. The processing workflow incorporates several new modules, designed to (i) efficiently match Friedel pairs in large s3DXRD datasets containing up to 108 diffraction peaks; (ii) assign phases to each pixel or voxel, resolving potential ambiguities arising from overlap in scattering angles between different crystallographic phases; and (iii) fit the crystal orientation and unit cell locally on a point-by-point basis. We demonstrate the effectiveness of our technique on fractured granite samples, highlighting the ability of the method to characterize complex geological materials and show their internal structure and mineral composition. Additionally, we include the characterization of a metal gasket made of a commercial aluminium alloy, which surrounded the granite sample during experiments. The results show the effectiveness of the technique in recovering information about the internal texture and residual strain of materials that have undergone high levels of plastic deformation.

Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach applies interatomic potentials to obtain solutions that are both physically sensible and in agreement with experiment. To expand the range of materials that can be studied with hybrid RMC, we have implemented a new interatomic potential constraint in RMCProfile that grants flexibility to apply potentials supported by the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular dynamics code. This includes machine learning interatomic potentials, which provide a pathway to applying hybrid RMC to materials without currently available interatomic potentials. To this end, we present a methodology to use RMC to train machine learning interatomic potentials for hybrid RMC applications.

In the conventional crucible structure for AlN crystal growth by physical vapor transport, owing to the long molecular transport path of Al vapor and the disruption of the gas flow by the presence of a deflector, the Al vapor easily forms polycrystals in the growth domain. The result is increased internal stress in the crystals and increased difficulty in growing large-sized crystals. On this basis, with the help of finite element simulations, a novel crucible structure is designed. This crucible not only optimizes the gas transport but also increases the radial gradient of the AlN crystal surface, making the enhanced growth rate in the central region more obvious. The thermal stresses between the deflector and the crystal are also reduced. High-quality AlN crystals with an FWHM of 79 arcsec were successfully grown with this structure, verifying the accuracy of finite element simulation of the growth of AlN crystals. Our work has important guiding significance for the growth of high-quality AlN crystals.

Painted artworks represent a significant group of cultural heritage artifacts, which are primarily admired because of their aesthetic quality. Nevertheless, the value of each particular painting depends also on what is known about it. Material investigation of paintings is one of the most reliable sources of information. Materials in painted artworks (i.e. panel, easel and miniature paintings, wall paintings, polychromed sculptures etc.) represent an extensive set of inorganic and organic phases, which are often present in complicated mixtures and exhibit characteristics reflecting their geological genesis (mineral pigments), manufacturing technology (artificial pigments), diverse biological nature (binders or dyes) or secondary changes (degradation or intentional later interventions). The analyses of paintings are often made challenging by the heterogeneous nature and minute size of micro-samples or, in some cases, even by the impossibility of sampling due to the preciousness, fragility or small dimensions of the artwork. This review demonstrates the successful implementation of laboratory X-ray powder micro-diffraction for material investigation of paintings, illustrating its efficiency for mineralogical analysis of (i) earth-based materials indicating the provenance of paintings, (ii) copper-based pigments pointing to their origin, and (iii) products of both salt corrosion and saponification enabling one to reveal the deterioration and probable original appearance of artworks.

This study introduces an alternative method to the Takagi–Taupin equations for investigating the dark-field X-ray microscopy (DFXM) of deformed crystals. In scenarios where dynamical diffraction cannot be disregarded, it is essential to assess the potential inaccuracies of data interpretation based on the kinematic diffraction theory. Unlike the Takagi–Taupin equations, this new method utilizes an exact dispersion relation, and a previously developed finite difference scheme with minor modifications is used for the numerical implementation. The numerical implementation has been validated by calculating the diffraction of a diamond crystal with three components, wherein dynamical diffraction is applicable to the first component and kinematic diffraction pertains to the remaining two. The numerical convergence is tested using diffraction intensities. In addition, the DFXM image of a diamond crystal containing a stacking fault is calculated using the new method and compared with the experimental result. The new method is also applied to calculate the DFXM image of a twisted diamond crystal, which clearly shows a result different from those obtained using the Takagi–Taupin equations.

Small-angle X-ray scattering (SAXS) is a widely used method for nanoparticle characterization. A common approach to analysing nanoparticles in solution by SAXS involves fitting the curve using a parametric model that relates real-space parameters, such as nanoparticle size and electron density, to intensity values in reciprocal space. Selecting the optimal model is a crucial step in terms of analysis quality and can be time-consuming and complex. Several studies have proposed effective methods, based on machine learning, to automate the model selection step. Deploying these methods in software intended for both researchers and industry raises several issues. The diversity of SAXS instrumentation requires assessment of the robustness of these methods on data from various machine configurations, involving significant variations in the q-space ranges and highly variable signal-to-noise ratios (SNR) from one data set to another. In the case of laboratory instrumentation, data acquisition can be time-consuming and there is no universal criterion for defining an optimal acquisition time. This paper presents an approach that revisits the nanoparticle model selection method proposed by Monge et al. [Acta Cryst. (2024), A80, 202–212], evaluating and enhancing its robustness on data from device configurations not seen during training, by expanding the data set used for training. The influence of SNR on predictor robustness is then assessed, improved, and used to propose a stopping criterion for optimizing the trade-off between exposure time and data quality.

Algebraic expressions for averaging linear and nonlinear stiffness tensors from general anisotropy to different effective symmetries (11 Laue classes elastically representing all 32 crystal classes, and two non-crystalline symmetries: isotropic and cylindrical) have been derived by automatic symbolic computations of the arithmetic mean over the set of rotational transforms determining a given symmetry. This approach generalizes the Voigt average to nonlinear constants and desired approximate symmetries other than isotropic, which can be useful for a description of textured polycrystals and rocks preserving some symmetry aspects. Low-symmetry averages have been used to derive averages of higher symmetry to speed up computations. Relationships between the elastic constants of each symmetry have been deduced from their corresponding averages by resolving the rank-deficient system of linear equations. Isotropy has also been considered in terms of generalized Lamé constants. The results are published in the form of appendices in the supporting information for this article and have been deposited in the Mendeley database.

The etoxazole metabolite R13, systematic name 4-(4-tert-butyl-2-ethoxyphenyl)-2-(2,6-difluorophenyl)oxazole (C21H21F2NO2), results from the oxidation of etoxazole, a chitin synthesis inhibitor belonging to the oxazoline class, widely used as an insecticide/acaricide since 1998. The structure of R13 features a central oxazole ring with attached 2,6-difluorophenyl and 4-t-butyl-2-ethoxyphenyl moieties. The overall conformation gives dihedral angles between these rings and the oxazole of 24.91 (5)° (with difluorophenyl) and 15.30 (6)° (with t-butyl-ethoxyphenyl), indicating an overall deviation from planarity. Additionally, torsion angles of the ethoxy and t-butyl groups define the orientation of these substituents relative to their benzene ring. In the crystal packing, no significant hydrogen bonds are present, but a Hirshfeld surface analysis highlights weak intermolecular contacts leading to π–π-stacked dimers linked by weak C—H...N contacts. The packing analysis confirms that most intermolecular interactions involve hydrogen atoms.

The title compound, [Ni(C40H30N2O2)] (1), with an optically active Schiff base ligand derived from 2-hydroxybenzophenone and (1S,2S)-1,2-diphenylethylenediamine, was crystallized as the solvent-free and ethanol solvate forms (1 and 1·2C2H5OH). In both structures, the two phenyl groups on the stereogenic centers of the O,N,N,O-tetradentate ligand are axially oriented, and the conformation of the central diamine chelate ring is λ. The circular dichroism (CD) spectra of 1 and the analogous nickel(II) complex [Ni(C30H26N2O2)] (2) in solution show partially similar patterns in the 350–450 nm range, but are mirror images in the longer wavelength region (450–650 nm). In the latter region, the sign of CD for these complexes is sensitive to the substituents on the C=N carbon atoms (phenyl for 1 and methyl for 2) rather than the diamine chelate ring conformation.

The African Light Source (AfLS) project is now almost eight years old. This article assesses the history, current context and future of the project. There is by now considerable momentum in building the user community, including deep training, facilitating access to current facilities, growing the scientific output, scientific networks and growing the local laboratory-scale research infrastructure. The Conceptual Design Report for the AfLS is in its final editing stages. This document specifies the socio-economic and scientific rationales and the technical aspects amongst others. The AfLS is supported by many national and Pan-African scientific professional bodies and voluntary associates across many scientific disciplines, and there are stakeholders throughout the continent and beyond. The current roadmap phases have expanded to include national and Pan-African level conversations with policy makers through new Strategic Task Force groups. The document summarizes this progress and discusses the future of the project.

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

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

Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacunae, voids that house osteocytes, and submicrometer-sized canaliculi that connect bone cells. Characterization of this network in three dimensions is crucial for many bone studies. To quantify X-ray Zernike phase-contrast nanotomography data, deep learning is used to isolate and assess porosity in artifact-laden tomographies of zebrafish bones. A technical solution is proposed to overcome the halo and shade-off domains in order to reliably obtain the distribution and morphology of the LCN in the tomographic data. Convolutional neural network (CNN) models are utilized with increasing numbers of images, repeatedly validated by `error loss' and `accuracy' metrics. U-Net and Sensor3D CNN models were trained on data obtained from two different synchrotron Zernike phase-contrast transmission X-ray microscopes, the ANATOMIX beamline at SOLEIL (Paris, France) and the P05 beamline at PETRA III (Hamburg, Germany). The Sensor3D CNN model with a smaller batch size of 32 and a training data size of 70 images showed the best performance (accuracy 0.983 and error loss 0.032). The analysis procedures, validated by comparison with human-identified ground-truth images, correctly identified the voids within the bone matrix. This proposed approach may have further application to classify structures in volumetric images that contain non-linear artifacts that degrade image quality and hinder feature identification.