Computational Materials Chemistry

This book provides a broad and nuanced overview of the achievements and legacy of Professor William (“Bill”) Goddard in the field of computational materials and molecular science. Leading researchers from around the globe discuss Goddard’s work and its lasting impacts, which can be seen in today’s cutting-edge chemistry, materials science, and biology techniques. Each section of the book closes with an outline of the prospects for future developments. In the course of a career spanning more than 50 years, Goddard’s seminal work has led to dramatic advances in a diverse range of science and engineering fields. Presenting scientific essays and reflections by students, postdoctoral associates, collaborators and colleagues, the book describes the contributions of one of the world’s greatest materials and molecular scientists in the context of theory, experimentation, and applications, and examines his legacy in each area, from conceptualization (the first mile) to developments and extensions aimed at applications, and lastly to de novo design (the last mile). Goddard’s passion for science, his insights, and his ability to actively engage with his collaborators in bold initiatives is a model for us all. As he enters his second half-century of scientific research and education, this book inspires future generations of students and researchers to employ and extend these powerful techniques and insights to tackle today’s critical problems in biology, chemistry, and materials. Examples highlighted in the book include new materials for photocatalysts to convert water and CO2 into fuels, novel catalysts for the highly selective and active catalysis of alkanes to valuable organics, simulating the chemistry in film growth to develop two-dimensional functional films, and predicting ligand–protein binding and activation to enable the design of targeted drugs with minimal side effects.

As a result of the advancements in algorithms and the huge increase in speed of computers over the past decade, electronic structure calculations have evolved into a valuable tool for characterizing surface species and for elucidating the pathways for their formation and reactivity. It is also now possible to calculate, including electric field effects, STM images for surface structures. To date the calculation of such images has been dominated by density functional methods, primarily because the computational cost of - curate wave-function based calculations using either realistic cluster or slab models would be prohibitive. DFT calculations have proven especially valuable for elucidating chemical processes on silicon and other semiconductor surfaces. However, it is also clear that some of the systems to which DFT methods have been applied have large non-dynamical correlation effects, which may not be properly handled by the current generation of Kohn-Sham-based density functionals. For example, our CASSCF calculations on the Si(001)/acetylene system reveal that at some geometries there is extensive 86 configuration mixing. This, in turn, could signal problems for DFT cal- lations on these systems. Some of these problem systems can be addressed using ONIOM or other “layering” methods, treating the primary region of interest with a CASMP2 or other multireference-based method, and treating the secondary region by a lower level of electronic structure theory or by use of a molecular mechanics method. ACKNOWLEDGEMENTS We wish to thank H. Jónsson, C. Sosa, D. Sorescu, P. Nachtigall, and T. -C.

New technologies are made possible by new materials, and until recently new materials could only be discovered experimentally. Recent advances in solving the crystal structure prediction problem means that the computational design of materials is now a reality. Computational Materials Discovery provides a comprehensive review of this field covering different computational methodologies as well as specific applications of materials design. The book starts by illustrating how and why first-principle calculations have gained importance in the process of materials discovery. The book is then split into three sections, the first exploring different approaches and ideas including crystal structure prediction from evolutionary approaches, data mining methods and applications of machine learning. Section two then looks at examples of designing specific functional materials with special technological relevance for example photovoltaic materials, superconducting materials, topological insulators and thermoelectric materials. The final section considers recent developments in creating low-dimensional materials. With contributions from pioneers and leaders in the field, this unique and timely book provides a convenient entry point for graduate students, researchers and industrial scientists on both the methodologies and applications of the computational design of materials.

Computational tools have been permanently deposited into the toolbox of theoretical chemists. The impact of new computational tools can hardly be overestimated, and their presence in research and applications is overwhelming. Theoretical methods such as quantum mechanics, molecular dynamics, and statistical mechanics have been successfully used to characterize chemical systems and to design new materials, drugs, and chemicals. This volume on Computational Material Sciences covers selected examples of notable applications of computational techniques to material science. The chapters contained in this volume include discussions of the phenomenon of chaos in chemistry, reaction network analysis, and mechanisms of formation of clusters. Details of more practical applications are also included in the form of reviews of computational design of new materials and the prediction of properties and structures of well known molecular assemblies. Current developments of effective computational methods, which will help in understanding, predicting, and optimizing periodic systems, nanostructures, clusters and model surfaces are also covered in this volume. Reviews of current computational methods applied in material science Reviews of practical applications of modelling of structures and properties of materials Cluster and periodical approaches

Emphasising essential methods and universal principles, this textbook provides everything students need to understand the basics of simulating materials behaviour. All the key topics are covered from electronic structure methods to microstructural evolution, appendices provide crucial background material, and a wealth of practical resources are available online to complete the teaching package. Modelling is examined at a broad range of scales, from the atomic to the mesoscale, providing students with a solid foundation for future study and research. Detailed, accessible explanations of the fundamental equations underpinning materials modelling are presented, including a full chapter summarising essential mathematical background. Extensive appendices, including essential background on classical and quantum mechanics, electrostatics, statistical thermodynamics and linear elasticity, provide the background necessary to fully engage with the fundamentals of computational modelling. Exercises, worked examples, computer codes and discussions of practical implementations methods are all provided online giving students the hands-on experience they need.

This book covers the essentials of Computational Science and gives tools and techniques to solve materials science problems using molecular dynamics (MD) and first-principles methods. The new edition expands upon the density functional theory (DFT) and how the original DFT has advanced to a more accurate level by GGA+U and hybrid-functional methods. It offers 14 new worked examples in the LAMMPS, Quantum Espresso, VASP and MedeA-VASP programs, including computation of stress-strain behavior of Si-CNT composite, mean-squared displacement (MSD) of ZrO2-Y2O3, band structure and phonon spectra of silicon, and Mo-S battery system. It discusses methods once considered too expensive but that are now cost-effective. New examples also include various post-processed results using VESTA, VMD, VTST, and MedeA.

Computational Materials Science: An Introduction covers the essentials of computational science and explains how computational tools and techniques work to help solve materials science problems. The book focuses on two levels of a materials system: the electronic structure level of nuclei and electrons and the atomistic/molecular level. It presents