A rational way to find the appropriate conditions to grow crystal samples for bio-crystallography is to determine the crystallization phase diagram, which allows precise control of the parameters affecting the crystal growth process. First, the nucleation is induced at supersaturated conditions close to the solubility boundary between the nucleation and metastable regions. Then, crystal growth is further achieved in the metastable zone – which is the optimal location for slow and ordered crystal expansion – by modulation of specific physical parameters. Recently, a prototype of an integrated apparatus for the rational optimization of crystal growth by mapping and manipulating temperature–precipitant–concentration phase diagrams has been constructed. Here, it is demonstrated that a thorough knowledge of the phase diagram is vital in any crystallization experiment. The relevance of the selection of the starting position and the kinetic pathway undertaken in controlling most of the final properties of the synthesized crystals is shown. The rational crystallization optimization strategies developed and presented here allow tailoring of crystal size and diffraction quality, significantly reducing the time, effort and amount of expensive protein material required for structure determination.

Hybrid photon-counting detectors are widely established at third-generation synchrotron facilities and the specifications of the Pilatus3 X CdTe were quickly recognized as highly promising in charge-density investigations. This is mainly attributable to the detection efficiency in the high-energy X-ray regime, in combination with a dynamic range and noise level that should overcome the perpetual problem of detecting strong and weak data simultaneously. These benefits, however, come at the expense of a persistent problem for high diffracted beam flux, which is particularly problematic in single-crystal diffraction of materials with strong scattering power and sharp diffraction peaks. Here, an in-depth examination of data collected on an inorganic material, FeSb2, and an organic semiconductor, rubrene, revealed systematic differences in strong intensities for different incoming beam fluxes, and the implemented detector intensity corrections were found to be inadequate. Only significant beam attenuation for the collection of strong reflections was able to circumvent this systematic error. All data were collected on a bending-magnet beamline at a third-generation synchrotron radiation facility, so undulator and wiggler beamlines and fourth-generation synchrotrons will be even more prone to this error. On the other hand, the low background now allows for an accurate measurement of very weak intensities, and it is shown that it is possible to extract structure factors of exceptional quality using standard crystallographic software for data processing (SAINT-Plus, SADABS and SORTAV), although special attention has to be paid to the estimation of the background. This study resulted in electron-density models of substantially higher accuracy and precision compared with a previous investigation, thus for the first time fulfilling the promise of photon-counting detectors for very accurate structure factor measurements.

High-quality single-crystal X-ray diffraction measurements are a prerequisite for obtaining precise and reliable structure data and electron densities. The single crystal should therefore fulfill several conditions, of which a regular defined shape is of particularly high importance for compounds consisting of heavy elements with high X-ray absorption coefficients. The absorption of X-rays passing through a 50 µm-thick LiNbO3 crystal can reduce the transmission of Mo Kα radiation by several tens of percent, which makes an absorption correction of the reflection intensities necessary. In order to reduce ambiguities concerning the shape of a crystal, used for the necessary absorption correction, a method for preparation of regularly shaped single crystals out of large samples is presented and evaluated. This method utilizes a focused ion beam to cut crystals with defined size and shape reproducibly and carefully without splintering. For evaluation, a single-crystal X-ray diffraction study using a laboratory diffractometer is presented, comparing differently prepared LiNbO3 crystals originating from the same macroscopic crystal plate. Results of the data reduction, structure refinement and electron density reconstruction indicate qualitatively similar values for all prepared crystals. Thus, the different preparation techniques have a smaller impact than expected. However, the atomic coordinates, electron densities and atomic charges are supposed to be more reliable since the focused-ion-beam-prepared crystal exhibits the smallest extinction influences. This preparation technique is especially recommended for susceptible samples, for cases where a minimal invasive preparation procedure is needed, and for the preparation of crystals from specific areas, complex material architectures and materials that cannot be prepared with common methods (breaking or grinding).

The fully automatic processing of crystals of macromolecules has presented a unique opportunity to gather information on the samples that is not usually recorded. This has proved invaluable in improving sample-location, characterization and data-collection algorithms. After operating for four years, MASSIF-1 has now processed over 56 000 samples, gathering information at each stage, from the volume of the crystal to the unit-cell dimensions, the space group, the quality of the data collected and the reasoning behind the decisions made in data collection. This provides an unprecedented opportunity to analyse these data together, providing a detailed landscape of macromolecular crystals, intimate details of their contents and, importantly, how the two are related. The data show that mosaic spread is unrelated to the size or shape of crystals and demonstrate experimentally that diffraction intensities scale in proportion to crystal volume and molecular weight. It is also shown that crystal volume scales inversely with molecular weight. The results set the scene for the development of X-ray crystallography in a changing environment for structural biology.

Reliable sample delivery and efficient use of limited beam time have remained bottlenecks for serial crystallography (SX). Using a high-intensity polychromatic X-ray beam in combination with a newly developed charge-integrating JUNGFRAU detector, we have applied the method of fixed-target SX to collect data at a rate of 1 kHz at a synchrotron-radiation facility. According to our data analysis for the given experimental conditions, only about 3 000 diffraction patterns are required for a high-quality diffraction dataset. With indexing rates of up to 25%, recording of such a dataset takes less than 30 s.

Radiation damage is the most fundamental limitation for achieving high resolution in electron cryo-microscopy (cryo-EM) of biological samples. The effects of radiation damage are reduced by liquid-helium cooling, although the use of liquid helium is more challenging than that of liquid nitrogen. To date, the benefits of liquid-nitrogen and liquid-helium cooling for single-particle cryo-EM have not been compared quantitatively. With recent technical and computational advances in cryo-EM image recording and processing, such a comparison now seems timely. This study aims to evaluate the relative merits of liquid-helium cooling in present-day single-particle analysis, taking advantage of direct electron detectors. Two data sets for recombinant mouse heavy-chain apoferritin cooled with liquid-nitrogen or liquid-helium to 85 or 17 K were collected, processed and compared. No improvement in terms of resolution or Coulomb potential map quality was found for liquid-helium cooling. Interestingly, beam-induced motion was found to be significantly higher with liquid-helium cooling, especially within the most valuable first few frames of an exposure, thus counteracting any potential benefit of better cryoprotection that liquid-helium cooling may offer for single-particle cryo-EM.

High-throughput X-ray crystal structures of protein–ligand complexes are critical to pharmaceutical drug development. However, cryocooling of crystals and X-ray radiation damage may distort the observed ligand binding. Serial femtosecond crystallography (SFX) using X-ray free-electron lasers (XFELs) can produce radiation-damage-free room-temperature structures. Ligand-binding studies using SFX have received only modest attention, partly owing to limited beamtime availability and the large quantity of sample that is required per structure determination. Here, a high-throughput approach to determine room-temperature damage-free structures with excellent sample and time efficiency is demonstrated, allowing complexes to be characterized rapidly and without prohibitive sample requirements. This yields high-quality difference density maps allowing unambiguous ligand placement. Crucially, it is demonstrated that ligands similar in size or smaller than those used in fragment-based drug design may be clearly identified in data sets obtained from <1000 diffraction images. This efficiency in both sample and XFEL beamtime opens the door to true high-throughput screening of protein–ligand complexes using SFX.

Rational structure-based drug design (SBDD) relies on the availability of a large number of co-crystal structures to map the ligand-binding pocket of the target protein and use this information for lead-compound optimization via an iterative process. While SBDD has proven successful for many drug-discovery projects, its application to G protein-coupled receptors (GPCRs) has been limited owing to extreme difficulties with their crystallization. Here, a method is presented for the rapid determination of multiple co-crystal structures for a target GPCR in complex with various ligands, taking advantage of the serial femtosecond crystallography approach, which obviates the need for large crystals and requires only submilligram quantities of purified protein. The method was applied to the human β2-adrenergic receptor, resulting in eight room-temperature co-crystal structures with six different ligands, including previously unreported structures with carvedilol and propranolol. The generality of the proposed method was tested with three other receptors. This approach has the potential to enable SBDD for GPCRs and other difficult-to-crystallize membrane proteins.

Tannerella forsythia is an oral dysbiotic periodontopathogen involved in severe human periodontal disease. As part of its virulence factor armamentarium, at the site of colonization it secretes mirolysin, a metallopeptidase of the unicellular pappalysin family, as a zymogen that is proteolytically auto-activated extracellularly at the Ser54–Arg55 bond. Crystal structures of the catalytically impaired promirolysin point mutant E225A at 1.4 and 1.6 Å revealed that latency is exerted by an N-terminal 34-residue pro-segment that shields the front surface of the 274-residue catalytic domain, thus preventing substrate access. The catalytic domain conforms to the metzincin clan of metallopeptidases and contains a double calcium site, which acts as a calcium switch for activity. The pro-segment traverses the active-site cleft in the opposite direction to the substrate, which precludes its cleavage. It is anchored to the mature enzyme through residue Arg21, which intrudes into the specificity pocket in cleft sub-site S1'. Moreover, residue Cys23 within a conserved cysteine–glycine motif blocks the catalytic zinc ion by a cysteine-switch mechanism, first described for mammalian matrix metallopeptidases. In addition, a 1.5 Å structure was obtained for a complex of mature mirolysin and a tetradecapeptide, which filled the cleft from sub-site S1' to S6'. A citrate molecule in S1 completed a product-complex mimic that unveiled the mechanism of substrate binding and cleavage by mirolysin, the catalytic domain of which was already preformed in the zymogen. These results, including a preference for cleavage before basic residues, are likely to be valid for other unicellular pappalysins derived from archaea, bacteria, cyanobacteria, algae and fungi, including archetypal ulilysin from Methanosarcina acetivorans. They may further apply, at least in part, to the multi-domain orthologues of higher organisms.

With the emergence of X-ray free-electron lasers, it is possible to investigate the structure of nanoscale samples by employing coherent diffractive imaging in the X-ray spectral regime. In this work, we developed a refinement method for structure reconstruction applicable to low-quality coherent diffraction data. The method is based on the gradient search method and considers the missing region of a diffraction pattern and the small number of detected photons. We introduced an initial estimate of the structure in the method to improve the convergence. The present method is applied to an experimental diffraction pattern of an Xe cluster obtained in an X-ray scattering experiment at the SPring-8 Angstrom Compact free-electron LAser (SACLA) facility. It is found that the electron density is successfully reconstructed from the diffraction pattern with a large missing region, with a good initial estimate of the structure. The diffraction pattern calculated from the reconstructed electron density reproduced the observed diffraction pattern well, including the characteristic intensity modulation in each ring. Our refinement method enables structure reconstruction from diffraction patterns under difficulties such as missing areas and low diffraction intensity, and it is potentially applicable to the structure determination of samples that have low scattering power.

This study describes a method to estimate the likelihood of success in determining a macromolecular structure by X-ray crystallography and experimental single-wavelength anomalous dispersion (SAD) or multiple-wavelength anomalous dispersion (MAD) phasing based on initial data-processing statistics and sample crystal properties. Such a predictive tool can rapidly assess the usefulness of data and guide the collection of an optimal data set. The increase in data rates from modern macromolecular crystallography beamlines, together with a demand from users for real-time feedback, has led to pressure on computational resources and a need for smarter data handling. Statistical and machine-learning methods have been applied to construct a classifier that displays 95% accuracy for training and testing data sets compiled from 440 solved structures. Applying this classifier to new data achieved 79% accuracy. These scores already provide clear guidance as to the effective use of computing resources and offer a starting point for a personalized data-collection assistant.

Characterizing and controlling the uniformity of nanoparticles is crucial for their application in science and technology because crystalline defects in the nanoparticles strongly affect their unique properties. Recently, ultra-short and ultra-bright X-ray pulses provided by X-ray free-electron lasers (XFELs) opened up the possibility of structure determination of nanometre-scale matter with Å spatial resolution. However, it is often difficult to reconstruct the 3D structural information from single-shot X-ray diffraction patterns owing to the random orientation of the particles. This report proposes an analysis approach for characterizing defects in nanoparticles using wide-angle X-ray scattering (WAXS) data from free-flying single nanoparticles. The analysis method is based on the concept of correlated X-ray scattering, in which correlations of scattered X-ray are used to recover detailed structural information. WAXS experiments of xenon nanoparticles, or clusters, were conducted at an XFEL facility in Japan by using the SPring-8 Ångstrom compact free-electron laser (SACLA). Bragg spots in the recorded single-shot X-ray diffraction patterns showed clear angular correlations, which offered significant structural information on the nanoparticles. The experimental angular correlations were reproduced by numerical simulation in which kinematical theory of diffraction was combined with geometric calculations. We also explain the diffuse scattering intensity as being due to the stacking faults in the xenon clusters.

Two commonly encountered bottlenecks in the structure determination of a protein by X-ray crystallography are screening for conditions that give high-quality crystals and, in the case of novel structures, finding derivatization conditions for experimental phasing. In this study, the phasing molecule 5-amino-2,4,6-triiodoisophthalic acid (I3C) was added to a random microseed matrix screen to generate high-quality crystals derivatized with I3C in a single optimization experiment. I3C, often referred to as the magic triangle, contains an aromatic ring scaffold with three bound I atoms. This approach was applied to efficiently phase the structures of hen egg-white lysozyme and the N-terminal domain of the Orf11 protein from Staphylococcus phage P68 (Orf11 NTD) using SAD phasing. The structure of Orf11 NTD suggests that it may play a role as a virion-associated lysin or endolysin.

Solute carriers are a large class of transporters that play key roles in normal and disease physiology. Among the solute carriers, heteromeric amino-acid transporters (HATs) are unique in their quaternary structure. LAT1–CD98hc, a HAT, transports essential amino acids and drugs across the blood–brain barrier and into cancer cells. It is therefore an important target both biologically and therapeutically. During the course of this work, cryo-EM structures of LAT1–CD98hc in the inward-facing conformation and in either the substrate-bound or apo states were reported to 3.3–3.5 Å resolution [Yan et al. (2019), Nature (London), 568, 127–130]. Here, these structures are analyzed together with our lower resolution cryo-EM structure, and multibody 3D auto-refinement against single-particle cryo-EM data was used to characterize the dynamics of the interaction of CD98hc and LAT1. It is shown that the CD98hc ectodomain and the LAT1 extracellular surface share no substantial interface. This allows the CD98hc ectodomain to have a high degree of movement within the extracellular space. The functional implications of these aspects are discussed together with the structure determination.

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image-processing workflows that allow the electron-microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 Å resolution β-galactosidase data set.

A nonlinear least-squares method for refining a parametric expression describing the estimated errors of reflection intensities in serial crystallographic (SX) data is presented. This approach, which is similar to that used in the rotation method of crystallographic data collection at synchrotrons, propagates error estimates from photon-counting statistics to the merged data. Here, it is demonstrated that the application of this approach to SX data provides better SAD phasing ability, enabling the autobuilding of a protein structure that had previously failed to be built. Estimating the error in the merged reflection intensities requires the understanding and propagation of all of the sources of error arising from the measurements. One type of error, which is well understood, is the counting error introduced when the detector counts X-ray photons. Thus, if other types of random errors (such as readout noise) as well as uncertainties in systematic corrections (such as from X-ray attenuation) are completely understood, they can be propagated along with the counting error, as appropriate. In practice, most software packages propagate as much error as they know how to model and then include error-adjustment terms that scale the error estimates until they explain the variance among the measurements. If this is performed carefully, then during SAD phasing likelihood-based approaches can make optimal use of these error estimates, increasing the chance of a successful structure solution. In serial crystallography, SAD phasing has remained challenging, with the few examples of de novo protein structure solution each requiring many thousands of diffraction patterns. Here, the effects of different methods of treating the error estimates are estimated and it is shown that using a parametric approach that includes terms proportional to the known experimental uncertainty, the reflection intensity and the squared reflection intensity to improve the error estimates can allow SAD phasing even from weak zinc anomalous signal.

Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Where the lack of a suitable homologue precludes conventional MR, one option is to predict the target structure using bioinformatics. Such modelling, in the absence of homologous templates, is called ab initio or de novo modelling. Recently, the accuracy of such models has improved significantly as a result of the availability, in many cases, of residue-contact predictions derived from evolutionary covariance analysis. Covariance-assisted ab initio models representing structurally uncharacterized Pfam families are now available on a large scale in databases, potentially representing a valuable and easily accessible supplement to the PDB as a source of search models. Here, the unconventional MR pipeline AMPLE is employed to explore the value of structure predictions in the GREMLIN and PconsFam databases. It was tested whether these deposited predictions, processed in various ways, could solve the structures of PDB entries that were subsequently deposited. The results were encouraging: nine of 27 GREMLIN cases were solved, covering target lengths of 109–355 residues and a resolution range of 1.4–2.9 Å, and with target–model shared sequence identity as low as 20%. The cluster-and-truncate approach in AMPLE proved to be essential for most successes. For the overall lower quality structure predictions in the PconsFam database, remodelling with Rosetta within the AMPLE pipeline proved to be the best approach, generating ensemble search models from single-structure deposits. Finally, it is shown that the AMPLE-obtained search models deriving from GREMLIN deposits are of sufficiently high quality to be selected by the sequence-independent MR pipeline SIMBAD. Overall, the results help to point the way towards the optimal use of the expanding databases of ab initio structure predictions.

Although often presented as taking single `snapshots' of the conformation of a protein, X-ray crystallography provides an averaged structure over time and space within the crystal. The important but difficult task of characterizing structural ensembles in crystals is typically limited to small conformational changes, such as multiple side-chain conformations. A crystallographic method was recently introduced that utilizes residual electron and anomalous density (READ) to characterize structural ensembles encompassing large-scale structural changes. Key to this method is an ability to accurately measure anomalous signals and distinguish them from noise or other anomalous scatterers. This report presents an optimized data-collection and analysis strategy for partially occupied iodine anomalous signals. Using the long-wavelength-optimized beamline I23 at Diamond Light Source, the ability to accurately distinguish the positions of anomalous scatterers with occupancies as low as ∼12% is demonstrated. The number and positions of these anomalous scatterers are consistent with previous biophysical, kinetic and structural data that suggest that the protein Im7 binds to the chaperone Spy in multiple partially occupied conformations. Finally, READ selections demonstrate that re-measured data using the new protocols are consistent with the previously characterized structural ensemble of the chaperone Spy with its client Im7. This study shows that a long-wavelength beamline results in easily validated anomalous signals that are strong enough to be used to detect and characterize highly disordered sections of crystal structures.

The conventional approach to search-model identification in molecular replacement (MR) is to screen a database of known structures using the target sequence. However, this strategy is not always effective, for example when the relationship between sequence and structural similarity fails or when the crystal contents are not those expected. An alternative approach is to identify suitable search models directly from the experimental data. SIMBAD is a sequence-independent MR pipeline that uses either a crystal lattice search or MR functions to directly locate suitable search models from databases. The previous version of SIMBAD used the fast AMoRe rotation-function search. Here, a new version of SIMBAD which makes use of Phaser and its likelihood scoring to improve the sensitivity of the pipeline is presented. It is shown that the additional compute time potentially required by the more sophisticated scoring is counterbalanced by the greater sensitivity, allowing more cases to trigger early-termination criteria, rather than running to completion. Using Phaser solved 17 out of 25 test cases in comparison to the ten solved with AMoRe, and it is shown that use of ensemble search models produces additional performance benefits.

Corrections are published for the article by Caldararu et al. [(2019), Acta Cryst. D75, 368–380].

Fragment-based molecular-replacement methods can solve a macromolecular structure quasi-ab initio. ARCIMBOLDO, using a common secondary-structure or tertiary-structure template or a library of folds, locates these with Phaser and reveals the rest of the structure by density modification and autotracing in SHELXE. The latter stage is challenging when dealing with diffraction data at lower resolution, low solvent content, high β-sheet composition or situations in which the initial fragments represent a low fraction of the total scattering or where their accuracy is low. SEQUENCE SLIDER aims to overcome these complications by extending the initial polyalanine fragment with side chains in a multisolution framework. Its use is illustrated on test cases and previously unknown structures. The selection and order of fragments to be extended follows the decrease in log-likelihood gain (LLG) calculated with Phaser upon the omission of each single fragment. When the starting substructure is derived from a remote homolog, sequence assignment to fragments is restricted by the original alignment. Otherwise, the secondary-structure prediction is matched to that found in fragments and traces. Sequence hypotheses are trialled in a brute-force approach through side-chain building and refinement. Scoring the refined models through their LLG in Phaser may allow discrimination of the correct sequence or filter the best partial structures for further density modification and autotracing. The default limits for the number of models to pursue are hardware dependent. In its most economic implementation, suitable for a single laptop, the main-chain trace is extended as polyserine rather than trialling models with different sequence assignments, which requires a grid or multicore machine. SEQUENCE SLIDER has been instrumental in solving two novel structures: that of MltC from 2.7 Å resolution data and that of a pneumococcal lipoprotein with 638 residues and 35% solvent content.

The information gained by making a measurement, termed the Kullback–Leibler divergence, assesses how much more precisely the true quantity is known after the measurement was made (the posterior probability distribution) than before (the prior probability distribution). It provides an upper bound for the contribution that an observation can make to the total likelihood score in likelihood-based crystallographic algorithms. This makes information gain a natural criterion for deciding which data can legitimately be omitted from likelihood calculations. Many existing methods use an approximation for the effects of measurement error that breaks down for very weak and poorly measured data. For such methods a different (higher) information threshold is appropriate compared with methods that account well for even large measurement errors. Concerns are raised about a current trend to deposit data that have been corrected for anisotropy, sharpened and pruned without including the original unaltered measurements. If not checked, this trend will have serious consequences for the reuse of deposited data by those who hope to repeat calculations using improved new methods.

Whole-mount (WM) platelet preparation followed by transmission electron microscopy (TEM) observation is the standard method currently used to assess dense granule (DG) deficiency (DGD). However, due to the electron-density-based contrast mechanism in TEM, other granules such as α-granules might cause false DG detection. Here, scanning transmission X-ray microscopy (STXM) was used to identify DGs and minimize false DG detection of human platelets. STXM image stacks of human platelets were collected at the calcium (Ca) L2,3 absorption edge and then converted to optical density maps. Ca distribution maps, obtained by subtracting the optical density maps at the pre-edge region from those at the post-edge region, were used to identify DGs based on the Ca richness. DGs were successfully detected using this STXM method without false detection, based on Ca maps for four human platelets. Spectral analysis of granules in human platelets confirmed that DGs contain a richer Ca content than other granules. The Ca distribution maps facilitated more effective DG identification than TEM which might falsely detect DGs. Correct identification of DGs would be important to assess the status of platelets and DG-related diseases. Therefore, this STXM method is proposed as a promising approach for better DG identification and diagnosis, as a complementary tool to the current WM TEM approach.

Active cathode particles are fundamental architectural units for the composite electrode of Li-ion batteries. The microstructure of the particles has a profound impact on their behavior and, consequently, on the cell-level electrochemical performance. LiCoO2 (LCO, a dominant cathode material) is often in the form of well-shaped particles, a few micrometres in size, with good crystallinity. In contrast to secondary particles (an agglomeration of many fine primary grains), which are the other common form of battery particles populated with structural and chemical defects, it is often anticipated that good particle crystallinity leads to superior mechanical robustness and suppressed charge heterogeneity. Yet, sub-particle level charge inhomogeneity in LCO particles has been widely reported in the literature, posing a frontier challenge in this field. Herein, this topic is revisited and it is demonstrated that X-ray absorption spectra on single-crystalline particles with highly anisotropic lattice structures are sensitive to the polarization configuration of the incident X-rays, causing some degree of ambiguity in analyzing the local spectroscopic fingerprint. To tackle this issue, a methodology is developed that extracts the white-line peak energy in the X-ray absorption near-edge structure spectra as a key data attribute for representing the local state of charge in the LCO crystal. This method demonstrates significantly improved accuracy and reveals the mesoscale chemical complexity in LCO particles with better fidelity. In addition to the implications on the importance of particle engineering for LCO cathodes, the method developed herein also has significant impact on spectro-microscopic studies of single-crystalline materials at synchrotron facilities, which is broadly applicable to a wide range of scientific disciplines well beyond battery research.

Enhancement of X-ray excited optical luminescence in a 100 µm-thick diamond plate by introduction of defect states via electron beam irradiation and subsequent high-temperature annealing is demonstrated. The resulting X-ray transmission-mode scintillator features a linear response to incident photon flux in the range 7.6 × 108 to 1.26 × 1012 photons s−1 mm−2 for hard X-rays (15.9 keV) using exposure times from 0.01 to 5 s. These characteristics enable a real-time transmission-mode imaging of X-ray photon flux density without disruption of X-ray instrument operation.

The first experimental results from a new transmissive diagnostic instrument for synchrotron X-ray beamlines are presented. The instrument utilizes a single-crystal chemical-vapour-deposition diamond plate as the detector material, with graphitic wires embedded within the bulk diamond acting as electrodes. The resulting instrument is an all-carbon transmissive X-ray imaging detector. Within the instrument's transmissive aperture there is no surface metallization that could absorb X-rays, and no surface structures that could be damaged by exposure to synchrotron X-ray beams. The graphitic electrodes are fabricated in situ within the bulk diamond using a laser-writing technique. Two separate arrays of parallel graphitic wires are fabricated, running parallel to the diamond surface and perpendicular to each other, at two different depths within the diamond. One array of wires has a modulated bias voltage applied; the perpendicular array is a series of readout electrodes. X-rays passing through the detector generate charge carriers within the bulk diamond through photoionization, and these charge carriers travel to the nearest readout electrode under the influence of the modulated electrical bias. Each of the crossing points between perpendicular wires acts as an individual pixel. The simultaneous read-out of all pixels is achieved using a lock-in technique. The parallel wires within each array are separated by 50 µm, determining the pixel pitch. Readout is obtained at 100 Hz, and the resolution of the X-ray beam position measurement is 600 nm for a 180 µm size beam.

The Advanced Photon Source 1-ID beamline, operating in the 40–140 keV X-ray energy range, has successfully employed continuously tunable saw-tooth refractive lenses to routinely deliver beams focused in both one and two dimensions to experiments for over 15 years. The practical experience of implementing such lenses, made of silicon and aluminium, is presented, including their properties, control, alignment, and diagnostic methods, achieving ∼1 µm focusing (vertically). Ongoing development and prospects towards submicrometre focusing at these high energies are also mentioned.

Serial crystallography is a powerful technique in structure determination using many small crystals at X-ray free-electron laser or synchrotron radiation facilities. The large diffraction data volumes require high-throughput software to preprocess the raw images for subsequent analysis. ClickX is a program designated for serial crystallography data preprocessing, capable of rapid data sorting for online feedback and peak-finding refinement by parameter optimization. The graphical user interface (GUI) provides convenient access to various operations such as pattern visualization, statistics plotting and parameter tuning. A batch job module is implemented to facilitate large-data-volume processing. A two-step geometry calibration for single-panel detectors is also integrated into the GUI, where the beam center and detector tilting angles are optimized using an ellipse center shifting method first, then all six parameters, including the photon energy and detector distance, are refined together using a residual minimization method. Implemented in Python, ClickX has good portability and extensibility, so that it can be installed, configured and used on any computing platform that provides a Python interface or common data file format. ClickX has been tested in online analysis at the Pohang Accelerator Laboratory X-ray Free-Electron Laser, Korea, and the Linac Coherent Light Source, USA. It has also been applied in post-experimental data analysis. The source code is available via https://github.com/LiuLab-CSRC/ClickX under a GNU General Public License.

Obtaining crystals and solving the phase problem remain major hurdles encountered by bio-crystallographers in their race to obtain new high-quality structures. Both issues can be overcome by the crystallophore, Tb-Xo4, a lanthanide-based molecular complex with unique nucleating and phasing properties. This article presents examples of new crystallization conditions induced by the presence of Tb-Xo4. These new crystalline forms bypass crystal defects often encountered by crystallographers, such as low-resolution diffracting samples or crystals with twinning. Thanks to Tb-Xo4's high phasing power, the structure determination process is greatly facilitated and can be extended to serial crystallography approaches.

Single-crystal elastic constants have been derived by lattice strain measurements using neutron diffraction on polycrystalline Ti-6Al-4V, Ti-6Al-2Sn-4Zr-6Mo and Ti-3Al-8V-6Cr-4Zr-4Mo alloy samples. A variety of model approximations for the grain-to-grain interactions, namely approaches by Voigt, Reuss, Hill, Kroener, de Wit and Matthies, including texture weightings, have been applied and compared. A load-transfer approach for multiphase alloys was also implemented and the results are compared with single-phase data. For the materials under investigation, the results for multiphase alloys agree well with the results for single-phase materials in the corresponding phases. In this respect, all eight elastic constants in the dual-phase Ti-6Al-2Sn-4Zr-6Mo alloy have been derived for the first time.

X-ray reflectivity (XRR) is a powerful and popular scattering technique that can give valuable insight into the growth behavior of thin films. This study shows how a simple artificial neural network model can be used to determine the thickness, roughness and density of thin films of different organic semiconductors [diindenoperylene, copper(II) phthalocyanine and α-sexithiophene] on silica from their XRR data with millisecond computation time and with minimal user input or a priori knowledge. For a large experimental data set of 372 XRR curves, it is shown that a simple fully connected model can provide good results with a mean absolute percentage error of 8–18% when compared with the results obtained by a genetic least mean squares fit using the classical Parratt formalism. Furthermore, current drawbacks and prospects for improvement are discussed.

It is shown that it is possible to perform combined X-ray and neutron single-crystal studies in the same diamond anvil cell (DAC). A modified Merrill–Bassett DAC equipped with an inflatable membrane filled with He gas has been developed. It can be used on laboratory X-ray and synchrotron diffractometers as well as on neutron instruments. The data processing procedures and a joint structural refinement of the high-pressure synchrotron and neutron single-crystal data are presented and discussed for the first time.

Knowledge of the appearance of texture components and fibres in pole figures, in inverse pole figures and in Euler space is fundamental for texture analysis. For cubic crystal systems, such as steels, an extensive literature exists and, for example, the book by Matthies, Vinel & Helming [Standard Distributions in Texture Analysis: Maps for the Case of Cubic Orthorhomic Symmetry, (1987), Akademie-Verlag Berlin] provides an atlas to identify texture components. For lower crystal symmetries, however, equivalent comprehensive overviews that can serve as guidance for the interpretation of experimental textures do not exist. This paper closes this gap by providing a set of scripts for the MTEX package [Bachmann, Hielscher & Schaeben (2010). Solid State Phenom. 160, 63–68] that allow the texture practitioner to compile such an atlas for a given material system, thus aiding orientation distribution function analysis also for non-cubic systems.

The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal and with unit-cell variations. A multi-stage data assembly method has previously been designed for microcrystal synchrotron crystallography. Here the strategy has been implemented as a Python program for microcrystal data assembly (PyMDA). PyMDA optimizes microcrystal data quality including weak anomalous signals through iterative crystal and frame rejections. Beyond microcrystals, PyMDA may be applicable for assembling data sets from larger crystals for improved data quality.

Molybdenum oxides and sulfides on various low-cost high-surface-area supports are excellent catalysts for several industrially relevant reactions. The surface layer structure of these materials is, however, difficult to characterize due to small and disordered MoOx domains. Here, it is shown how X-ray total scattering can be applied to gain insights into the structure through differential pair distribution function (d-PDF) analysis, where the scattering signal from the support material is subtracted to obtain structural information on the supported structure. MoOx catalysts supported on alumina nanoparticles and on zeolites are investigated, and it is shown that the structure of the hydrated molybdenum oxide layer is closely related to that of disordered and polydisperse polyoxometalates. By analysing the PDFs with a large number of automatically generated cluster structures, which are constructed in an iterative manner from known polyoxometalate clusters, information is derived on the structural motifs in supported MoOx.

In order to improve the instrumental accessibility of neutron diffraction techniques, many emerging compact neutron sources and in-house neutron diffractometers are being developed, even though the precision level of neutron diffraction experiments performed on such instruments was thought to be incomparable with that of large-scale neutron facilities. As a challenging project, the RIKEN accelerator-driven compact neutron source (RANS) was employed here to establish the technical environment for texture measurements, and the recalculated pole figures and orientation distribution functions of an interstitial-free steel sheet obtained from RANS were compared with the results from another two neutron diffractometers well established for texture measurement. These quantitative comparisons revealed that the precise neutron diffraction texture measurement at RANS has been realized successfully, and the fine region division of the neutron detector panel is invaluable for improving the stereographic resolution of texture measurements. Moreover, through selectively using the parts of the obtained neutron diffraction patterns that exhibit good statistics, the Rietveld texture analysis improves the reliability of the texture measurement to a certain extent. These technical research results may accelerate the development of other easily accessible techniques for evaluation of engineering materials using compact neutron sources, and also help to improve the data-collection efficiency for various time-resolved scattering experiments at large-scale neutron facilities.

This paper reports an Fe-added Y2O3 crucible which is capable of balancing the solution spontaneously and is employed to effectively enhance the homogeneity of YBa2(Cu1−xFex)3O7−δ single crystals.

The unique nucleating and phasing capabilities of the crystallophore, Tb-Xo4, are illustrated through challenging cases.

Single-crystalline-like thin films composed of crystallographically aligned grains are a new prototype of 2D materials developed recently for low-cost and high-performance flexible electronics as well as second-generation high-temperature superconductors. In this work, significant texture improvement in single-crystalline-like materials is achieved through growth of a 330 nm-thick silver layer.

The sin2ψ and cosα methods are compared via diffracting-grain identification from electron backscatter diffraction maps. Artificial textures created by the X-ray diffraction measurements are plotted and X-ray elastic constants of the diffracting-grain sets are computed.

This study demonstrates a new preparation method for single-crystal X-ray diffraction samples using a focused ion beam. The results of the structure determination and electron density maps with differently prepared samples are discussed, to evaluate this new method.

This article describes rational strategies for the optimization of crystal growth using precise in situ control of the temperature and chemical composition of the crystallization solution through dialysis, to generate crystals of the specific sizes required for different downstream structure determination approaches.

Detailed analysis of the high-flux deficiencies of pixel-array detectors leads to a protocol for the measurement of structure factors of unprecedented accuracy even for inorganic materials, and this significantly advances the prospects for experimental electron-density investigations.

The diffraction response of a single crystal to electric field measured by X-ray diffraction by angles close to π. Such schemes allow one to determine with high (~ 10–5–10–6) accuracy the relative changes in the lattice constant.

Hydrogen is present in almost all of the molecules in living things. It is very reactive and forms bonds with most of the elements, terminating their valences and enhancing their chemistry. X-ray diffraction is the most common method for structure determination. It depends on scattering of X-rays from electron density, which means the single electron of hydrogen is difficult to detect. Generally, neutron diffraction data are used to determine the accurate position of hydrogen atoms. However, the requirement for good quality single crystals, costly maintenance and the limited number of neutron diffraction facilities means that these kind of results are rarely available. Here it is shown that the use of Transferable Aspherical Atom Model (TAAM) instead of Independent Atom Model (IAM) in routine structure refinement with X-ray data is another possible solution which largely improves the precision and accuracy of X—H bond lengths and makes them comparable to averaged neutron bond lengths. TAAM, built from a pseudoatom databank, was used to determine the X—H bond lengths on 75 data sets for organic molecule crystals. TAAM parametrizations available in the modified University of Buffalo Databank (UBDB) of pseudoatoms applied through the DiSCaMB software library were used. The averaged bond lengths determined by TAAM refinements with X-ray diffraction data of atomic resolution (dmin ≤ 0.83 Å) showed very good agreement with neutron data, mostly within one single sample standard deviation, much like Hirshfeld atom refinement (HAR). Atomic displacements for both hydrogen and non-hydrogen atoms obtained from the refinements systematically differed from IAM results. Overall TAAM gave better fits to experimental data of standard resolution compared to IAM. The research was accompanied with development of software aimed at providing user-friendly tools to use aspherical atom models in refinement of organic molecules at speeds comparable to routine refinements based on spherical atom model.

Transferable Aspherical Atom Model (TAAM) instead of Independent Atom Model (IAM) applied through DiSCaMB software library in the structure refinement against X-ray diffraction data largely improves the X—H bond lengths and make them comparable to the averaged neutron bond lengths.

A single-chain, tailless Xenopus laevis H2A/H2B dimer construct (scH2BH2A) was engineered by directly fusing the C-terminus of H2B to the N-terminus of H2A without an artificial linker sequence. A high-resolution crystal structure of scH2BH2A shows that it adopts a nearly identical fold to that of nucleosomal H2A/H2B and may be useful for future structural studies of many H2A/H2B-interacting proteins.

Cytisine, a natural product with high affinity for clinically relevant nicotinic acetylcholine receptors (nAChRs), is used as a smoking-cessation agent. The compound displays an excellent clinical profile and hence there is an interest in derivatives that may be further improved or find use in the treatment of other conditions. Here, the binding of a cytisine derivative modified by the addition of a 3-(hydroxypropyl) moiety (ligand 4) to Aplysia californica acetylcholine-binding protein (AcAChBP), a surrogate for nAChR orthosteric binding sites, was investigated. Isothermal titration calorimetry revealed that the favorable binding of cytisine and its derivative to AcAChBP is driven by the enthalpic contribution, which dominates an unfavorable entropic component. Although ligand 4 had a less unfavorable entropic contribution compared with cytisine, the affinity for AcAChBP was significantly diminished owing to the magnitude of the reduction in the enthalpic component. The high-resolution crystal structure of the AcAChBP–4 complex indicated close similarities in the protein–ligand interactions involving the parts of 4 common to cytisine. The point of difference, the 3-(hydroxypropyl) substituent, appears to influence the conformation of the Met133 side chain and helps to form an ordered solvent structure at the edge of the orthosteric binding site.