Prediction And Calculation Of Crystal Structures

The series Topics in Current Chemistry presents critical reviews of the present and future trends in modern chemical research. The scope of coverage is all areas of chemical science including the interfaces with related disciplines such as biology, medicine and materials science. The goal of each thematic volume is to give the non-specialist reader, whether in academia or industry, a comprehensive insight into an area where new research is emerging which is of interest to a larger scientific audience. Each review within the volume critically surveys one aspect of that topic and places it within the context of the volume as a whole. The most significant developments of the last 5 to 10 years are presented using selected examples to illustrate the principles discussed. The coverage is not intended to be an exhaustive summary of the field or include large quantities of data, but should rather be conceptual, concentrating on the methodological thinking that will allow the non-specialist reader to understand the information presented. Contributions also offer an outlook on potential future developments in the field. Review articles for the individual volumes are invited by the volume editors. Readership: research chemists at universities or in industry, graduate students.

The term “first-principles calculations” is a synonym for the numerical determination of the electronic structure of atoms, molecules, clusters, or materials from ‘first principles’, i.e., without any approximations to the underlying quantum-mechanical equations. Although numerous approximate approaches have been developed for small molecular systems since the late 1920s, it was not until the advent of the density functional theory (DFT) in the 1960s that accurate “first-principles” calculations could be conducted for crystalline materials. The rapid development of this method over the past two decades allowed it to evolve from an explanatory to a truly predictive tool. Yet, challenges remain: complex chemical compositions, variable external conditions (such as pressure), defects, or properties that rely on collective excitations—all represent computational and/or methodological bottlenecks. This Special Issue comprises a collection of papers that use DFT to tackle some of these challenges and thus highlight what can (and cannot yet) be achieved using first-principles calculations of crystals.

This volume gathers key researchers representing the full scientific scope of the crystal structure prediction.

The prediction of crystal structures from first principles has been one of the grand challenges for computational methods in chemistry and materials science. The goal of being able to reliably predict crystal structures at an atomistic level of detail, given only the chemical composition as input, presents several challenges. A solution to the crystal structure prediction challenge requires advances in several areas of computational chemistry. This volume gathers key researchers representing the full scientific scope of the topic, including the developers of methods and software, those developing the application of the methods and interested experimentalists who may benefit from advances in predictive computational methods. This volume will appeal to researchers from computational chemistry, informatics, physics and materials science. Applications of crystal structure prediction methods also cover several fields, including crystallography, crystal engineering, mineralogy and pharmaceutical materials. The topics covered in this volume include: Structure searching methods ; Crystal structure evaluation: calculating relative stabilities and other criteria ; Applications of crystal structure prediction: organic molecular structures ; Applications of crystal structure prediction: inorganic and network structures.

Gathering leading specialists in the field of structure prediction, this book provides a unique view of this complex and rapidly developing field, reflecting the numerous viewpoints of the different authors. A summary of the major achievements over the last few years and of the challenges still remaining makes this monograph very timely.

A molecule can crystallise in more than one crystal structure, a common phenomenon in organic compounds known as polymorphism. Different polymorphic forms may have significantly different physical properties, and a reliable prediction would be beneficial to the pharmaceutical industry. However, crystal structure prediction (CSP) based on the knowledge of the chemical structure had long been considered impossible. Previous failures of some CSP attempts led to speculation that the thermodynamic calculations in CSP methodologies failed to predict the kinetically favoured structures. Similarly, regarding the stabilities of co-crystals relative to their pure components, the results from lattice energy calculations and full CSP studies were inconclusive. In this thesis, these problems are addressed using the state-of-the-art CSP methodology implemented in the GRACE software. Firstly, it is shown that the low-energy predicted structures of four organic molecules, which have previously been considered difficult for CSP, correspond to their experimental structures. The possible outcomes of crystallisation can be reliably predicted by sufficiently accurate thermodynamic calculations. Then, the polymorphism of 5- chloroaspirin is investigated theoretically. The order of polymorph stability is predicted correctly and the isostructural relationships between a number of predicted structures and the experimental structures of other aspirin derivatives are established. Regarding the stabilities of co-crystals, 99 out of 102 co-crystals and salts of nicotinamide, isonicotinamide and picolinamide reported in the Cambridge Structural Database (CSD) are found to be more stable than their corresponding co-formers. Finally, full CSP studies of two co-crystal systems are conducted to explain why the co-crystals are not easily obtained experimentally.

A unique and timely book providing an overview of both the methodologies and applications of computational materials design.

The term "first-principles calculations" is a synonym for the numerical determination of the electronic structure of atoms, molecules, clusters, or materials from 'first principles', i.e., without any approximations to the underlying quantum-mechanical equations. Although numerous approximate approaches have been developed for small molecular systems since the late 1920s, it was not until the advent of the density functional theory (DFT) in the 1960s that accurate "first-principles" calculations could be conducted for crystalline materials. The rapid development of this method over the past two decades allowed it to evolve from an explanatory to a truly predictive tool. Yet, challenges remain: complex chemical compositions, variable external conditions (such as pressure), defects, or properties that rely on collective excitations-all represent computational and/or methodological bottlenecks. This Special Issue comprises a collection of papers that use DFT to tackle some of these challenges and thus highlight what can (and cannot yet) be achieved using first-principles calculations of crystals.

Despite significant progress made in the last twenty years, the crystal structure prediction (CSP) of organic molecular solids remains challenging, as the demand to predict more complex crystal structures increases. On the one hand, relative energies between candidate crystal structures generated during a CSP protocol must be calculated accurately; on the other, the complexity of the crystal-energy landscape imposes stringent limitations on the method's computational cost. While plane-wave density-functional theory (DFT) methods have become the workhorse for the final stages of CSP protocols, due to their balance between high accuracy and efficiency, they remain prohibitively expensive during the early and intermediate stages. The primary aim of this thesis is the development of composite approaches for CSP, which comprise a geometry optimization using a low-cost method followed by a single- point energy calculation using plane-wave DFT with the exchange-hole dipole moment (XDM) dispersion model. The composite approaches were first tested on small molecular solids; assessment based on their abilities to produce absolute lattice energies was found to be misleading, and relative lattice energies provided a much better indicator of performance in a CSP context. To allow use of the XDM dispersion model with low-level methods, it was implemented in the SIESTA code, which uses numerical finite-support local orbitals to reduce the computational cost of the calculation. Composite approaches making use of the same DFT-D method both for low- and high-level DFT frameworks yielded the best ac- curacy, while remaining significantly cheaper than performing full geometry optimizations with plane-wave DFT. The composite approaches were then successfully employed for CSP of organic molecules with applications ranging from chiral organic semiconductors to pharmaceutical solids. Secondary objectives of this thesis sought to offer insight as to whether certain classes of solid-state materials are not appropriate benchmarks for method validation, and whether DFT-D methods are always suitable to describe all molecular crystals of interest. In particular, using compounds that form polytypes, e.g., crystalline aspirin, to validate com- putational methods was found to be inadvisable due to their high geometric and energetic similarity. Also, delocalization error, an often-overlooked limitation of most DFT methods, affected the correct identification of the protonation site in multicomponent acid-base crystals. This error greatly affects the reliability of these methods for validation of experi- mental (or the prediction of new) crystal structures. Overall, the work presented in this dissertation provides appropriate methodological and benchmarking tools to accelerate the intermediate stages of CSP protocols, while retaining high levels of accuracy and reliability in the crystal-energy landscapes generated, ultimately enabling the study of increasingly complex molecular crystals.

Multiscale simulations of atomistic/continuum coupling in computational materials science, where the scale expands from macro-/micro- to nanoscale, has become a hot research topic. These small units, usually nanostructures, are commonly anisotropic. The development of molecular modeling tools to describe and predict the mechanical properties of structures reveals an undeniable practical importance. Typical anisotropic structures (e.g. cubic, hexagonal, monoclinic) using DFT, MD, and atomic finite element methods are especially interesting, according to the modeling requirement of upscaling structures. It therefore connects nanoscale modeling and continuous patterns of deformation behavior by identifying relevant parameters from smaller to larger scales. These methodologies have the prospect of significant applications. I would like to recommend this book to both beginners and experienced researchers.