Considerable effort has been invested in developing methods for predicting the crystalline structure(s) of a given compound, ideally starting from no more than a structural formula of the molecule. Reliable computational predictions would be of great value in many areas of materials chemistry, from the design of materials with novel properties to the avoidance of an undesirable change of form in the late stages of development of an industrially important molecule. Methods used in crystal structure prediction are reviewed, with particular focus on the most common approach - global lattice energy minimization. Progress and current limitations are highlighted, with reference to examples from the literature and the results of blind tests organized to objectively monitor developments in the field.
This article provides, in tutorial style, a review of X-ray scattering methods commonly used to characterise nanoparticles and gives numerous case studies of basic science and industrial applications right up to the present. It is divided into two major sections, broadly covering X-ray diffraction and small-angle X-ray scattering. Each section begins with a brief introduction to the technique and the information that can be obtained by using it, followed by a discussion on experimental considerations, with a particular focus on nanoparticle characterisation. The techniques and analysis methods are demonstrated by way of examples of a wide variety of nanoparticle materials and synthesis methods. Recent advances in related techniques such as anomalous scattering and pair distribution function analysis are also described and discussed.
The broad range of applications of synchrotron and neutron scattering in the investigation of soft condensed matter is reviewed. Appropriate combinations of these techniques allow probing the structure and dynamics of these complex systems from sub-nm to micron size scales and picoseconds to seconds and longer time ranges. Applications include a myriad of systems such as polymers, colloids, surfactants, phospholipids, biological macromolecules and functional materials both in bulk and at interfaces. Most studies are performed in situ under the real thermodynamic state of the given system and large ensemble averaged information is readily obtained. The new generations of synchrotron and neutron sources open possibilities for investigating more complex soft matter systems in hitherto unexplored dynamical states.
Over the 100 years since the discovery of the diffraction of X-rays by crystals, structure determination based on the analysis of Bragg peaks has grown into a very precise, widely applicable, and definitive tool. This conventional crystallography is based on the assumption that a crystal consists of a three-dimensional array of identical units. Real materials, however, only approximate this ideal and their diffraction patterns contain, in addition to sharp Bragg peaks, a weak continuous background known as diffuse scattering. Diffuse scattering occurs when there are departures of any kind from the ideal lattice. The properties of many important materials are dependent not simply on the average crystal structure yielded by the Bragg analysis but are often crucially dependent on the departures from ideality (disorder) that can only be revealed by analysis of the diffuse scattering. Diffuse scattering has been known and studied since the very earliest days of crystallography but because of the generally very low intensities and the diversity of effects that can give rise to it, the field has largely remained the realm of a relatively few specialist research groups. However, in recent years with the advent of synchrotron sources, latest high-resolution and high-dynamic-range X-ray pixel detectors and powerful computers for analysis and modelling, the problems that limited development of diffuse scattering methods have now largely been solved. Current methods are now capable of tackling virtually any disorder problem to yield details of structure and dynamics that goes far beyond the confines of the average unit cell description of structure. In this paper, we outline how diffuse scattering methods developed over the course of a century since the birth of X-ray crystallography and review the wide range of different areas and materials to which the methods have been applied.
Metals are present in more than one-third of all proteins as they occur in nature, and are usually important in biological function or maintenance of the structure. Some are present as cations, directly associated with amino acid functional groups of the protein, others within small molecule cofactors associated with the protein. For the 10 metals commonly found as cations, Na, Mg, K, Ca, Mn, Fe, Co, Ni, Cu and Zn, a survey is given of occurrence, relative frequencies of both metal and donor atom or group type, and geometry of coordination. The survey is based on crystal structure information deposited in the Protein Data Bank (PDB) [Berman, H.; Henrick, K.; Nakamura, H.; Markley, J.L. The Worldwide Protein Data Bank (wwPDB): Ensuring a Single, Uniform Archive of PDB Data. Nucleic Acids Res. 2007, 35, D301-D303]. The precision and reliability of this information is assessed in detail. Illustrative examples are given for each metal, including, usually, details of the structure of the metal site in relation to the whole protein and to its function; there are comparisons between metals and descriptions of features such as binding to carboxylate and multiple metal sites close to each other. Metals found within cofactors which associate with the protein, most notably Mo, are included within these examples. Also included briefly are the prediction of metal sites in proteins resulting from genomic synthesis, information which can be derived from methods other than X-ray diffraction of crystals, and metal-protein systems which do not occur naturally.
X-ray crystallography is one of the most popular analytical methods, and with the advent of area detectors in the 1990s single crystal X-ray structure determination has become commonplace. Initially, the method was reserved for the expert, but hard- and software improvements of the last couple of decades have enabled scientists who are not formally trained in crystallography to determine crystal structures as well. This has led to an explosion of the number of crystal structures and, unfortunately, also of the number of incorrect structures submitted to scientific journals. It is evident that (semi)automated structure determination works only for routine structures. In more complex cases, such as structures with disorders, pseudo-symmetry or twinning, crystallographic knowledge, refinement skills and experience are still vital for obtaining high-quality, publication-grade crystal structures. This article is meant to offer a few suggestions to scientists who are using crystallography as part of their research, as an ancillary-science so to speak, hoping to help improve the quality of their crystal structures.
Since there is now a growing wish by referees to judge the underpinning data for a submitted article, it is timely to provide a summary of the data evaluation checks required to be done by a referee. As these checks will vary from field to field, this article focuses on the needs of biological X-ray crystallography articles, which is the predominantly used method leading to depositions in the PDB. These checks necessarily include that a referee scrutinizes the PDB validation report for each crystal structure accompanying the article submission. A referee would also undertake one cycle of model refinement of the authors' biological macromolecule coordinates against the authors' processed diffraction data and assess the model and Fo-Fc electron density maps. If the referee deems necessary, the raw diffraction data images should be reprocessed (e.g. to a different diffraction resolution). The organization of practical referee skills training can be via the crystallography associations.
Refinement of macromolecular X-ray crystal structures involves using complex software with hundreds of different settings. The complexity of underlying concepts and the sheer amount of instructions may make it difficult for less experienced crystallographers to achieve optimal results in their refinements. This tutorial review offers guidelines for choosing the best settings for the reciprocal-space refinement of macromolecular models and provides practical tips for manual model correction. To help aspiring crystallographers navigate the process, some of the most practically important concepts of protein structure refinement are described. Among the topics covered are the use and purpose of R-free, geometrical restraints, restraints on atomic displacement parameters (ADPs), refinement weights, various parametrizations of ADPs (full anisotropic refinement and TLS), and omit maps. We also give practical tips for manual model correction in Coot, modelling of side-chains with poor or missing density, and ligand identification, fitting, and refinement.
After the discovery of X-ray diffraction by crystals, amino acids were among the first organic compounds to have their solid-state structures investigated. The Cambridge Structural Database now contains more than 3500 entries for α-amino acids alone. After a short introduction dealing with the early history of X-ray structure determination, this review provides a classification of amino acid structures, describes essential structural elements, especially hydrogen bonding preferences and coordination to metal ions, and considers recent investigations on phase transitions as the result of extreme temperatures or pressure.
InGenious, so far the largest European education project clearly indicated one of the most important questions of modern education: optimizing the role of industry in education in STEM-fields (science, technology, engineering and mathematics). In this context, discussing the role of industry in crystallographic education could help to optimize future practices in the field. In an attempt to tackle this complex topic, first part of this review assesses definitions of crystallography, crystallographer and education approaches, and deducts questions on the challenges and opportunities of the contemporary crystallographic education. In the second part, some of these questions are answered by examining current and future roles of industry in crystallographic education: sponsorships, active teaching and technology transfer.
The principal method used today for single crystal X-ray data collection is the Arndt-Wonacott screenless rotation method formalized in the late 1970s, but the physical hardware used now would be barely recognizable to scientists at that time. However, the technique of rotating a crystal around a single goniostat axis, illuminating it with monochromatic radiation, and collecting the data on a flat detector is identical. Indeed, this would not have been very surprising to the pioneers of X-ray crystallography early in the Twentieth Century, since the elements of this method were available in the early days of the science. In a sense, therefore, we have come full circle after utilizing a variety of different experimental methods and equipment, and the question arises; 'how did we get here?'; after all, there were long periods in our science where we used point detectors or curved area detectors, or using polychromatic X-rays and stationary crystals. This review was originally presented at ECM31 in Oviedo, Spain in August 2018 under the title `Vagando entre los picos ¿cómo llegué hastaaquí? Improving methods in data collection and processing'; the Spanish texttranslates as 'Wandering amongst the peaks - how did I get here?'.
Refinement of atomic models is a necessary step in solving the macromolecular structure by X-ray diffraction methods. Nowadays, high automation and well-developed interfaces give a possibility to use the most popular refinement programs as black boxes. Nevertheless, working with complex objects requires an understanding of the internal structure and principles of operation of these programs and critical assessment of the results of refinement. In this review, we discuss the basic principles of the organization of refinement programs and the history of their improvement and development, as the studied objects became more and more complicated. The discussions are kept at the level of basic mathematic knowledge avoiding unnecessary formalism and too detailed expressions.
The portfolio of available synchrotron radiation techniques is increasing notably for cements and pastes. Furthermore, sometimes the terminology is confusing and an overall picture highlighting similarities and differences of related techniques was lacking. Therefore, the main objective of this work is to review recent advances in synchrotron techniques providing a comprehensive overview. This work is not intended to gather all publications in cement chemistry but to give a unified picture through selected examples. Crystallographic techniques are used for structure determination, quantitative phase analyses and microstructure characterization. These studies are not only carried out in standard conditions but synchrotron techniques are especially suited to non-ambient conditions: high temperatures and pressures, hydration, etc., and combinations. Related crystallographic techniques, like Pair Distribution Function, are being used for the analysis of ill-crystalline phase(s). Furthermore, crystallographic tools are also employed in imaging techniques including scanning diffraction microscopy and tomography and coherent diffraction imaging. Other synchrotron techniques are also reviewed including X-rays absorption spectroscopy for local structure and speciation characterizations; small angle X-ray scattering for microstructure analysis and several imaging techniques for microstructure quantification: full-field soft and hard X-ray nano-tomographies; scanning infrared spectro-microscopy; scanning transmission and fluorescence X-ray tomographies. Finally, a personal outlook is provided.
In this review the state of the art in metrics for single crystal diffraction data and suggested new developments are described. The focus is on how these metrics can help or prevent not only to describe the data but also to give hints towards unresolved modelling problems, identifying systematic errors and their sources.