Exploring Chemical Concepts Through Theory and Computation

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Publisher : John Wiley & Sons
ISBN 13 : 3527352481
Total Pages : 594 pages
Book Rating : 4.5/5 (273 download)

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Book Synopsis Exploring Chemical Concepts Through Theory and Computation by : Shubin Liu

Download or read book Exploring Chemical Concepts Through Theory and Computation written by Shubin Liu and published by John Wiley & Sons. This book was released on 2024-10-21 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep, theoretical resource on the essence of chemistry, explaining the sixteen most important concepts including redox states and bond types Exploring Chemical Concepts Through Theory and Computation provides a comprehensive account of how the three widely used theoretical frameworks of valence bond theory, molecular orbital theory, and density functional theory, along with a variety of important chemical concepts, can between them describe and efficiently and reliably predict key chemical parameters and phenomena. By comparing the three main theoretical frameworks, readers will become competent in choosing the right modeling approach for their task. The authors go beyond a simple comparison of existing algorithms to show how data-driven theories can explain why chemical compounds behave the way they do, thus promoting a deeper understanding of the essence of chemistry. The text is contributed to by top theoretical and computational chemists who have turned computational chemistry into today's data-driven and application-oriented science. Exploring Chemical Concepts Through Theory and Computation discusses topics including: Orbital-based approaches, density-based approaches, chemical bonding, partial charges, atoms in molecules, oxidation states, aromaticity and antiaromaticity, and acidity and basicity Electronegativity, hardness, softness, HSAB, sigma-hole interactions, charge transport and energy transfer, and homogeneous and heterogeneous catalysis Electrophilicity, nucleophilicity, cooperativity, frustration, homochirality, and energy decomposition Chemical concepts in solids, excited states, spectroscopy and machine learning, and catalysis and machine learning, and as well as key connections between related concepts Aimed at both novice and experienced computational, theoretical, and physical chemists, Exploring Chemical Concepts Through Theory and Computation is an essential reference to gain a deeper, more advanced holistic understanding of the field of chemistry as a whole.

Machine Learning in Chemistry

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Publisher : American Chemical Society
ISBN 13 : 0841299005
Total Pages : 189 pages
Book Rating : 4.8/5 (412 download)

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Book Synopsis Machine Learning in Chemistry by : Jon Paul Janet

Download or read book Machine Learning in Chemistry written by Jon Paul Janet and published by American Chemical Society. This book was released on 2020-05-28 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important

2D Metal Carbides and Nitrides (MXenes)

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Publisher : Springer Nature
ISBN 13 : 3030190269
Total Pages : 530 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis 2D Metal Carbides and Nitrides (MXenes) by : Babak Anasori

Download or read book 2D Metal Carbides and Nitrides (MXenes) written by Babak Anasori and published by Springer Nature. This book was released on 2019-10-30 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the rapidly expanding field of two-dimensional (2D) transition metal carbides and nitrides (MXenes). It covers fundamental knowledge on synthesis, structure, and properties of these new materials, and a description of their processing, scale-up and emerging applications. The ways in which the quickly expanding family of MXenes can outperform other novel nanomaterials in a variety of applications, spanning from energy storage and conversion to electronics; from water science to transportation; and in defense and medical applications, are discussed in detail.

Materials Discovery and Design

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Publisher : Springer
ISBN 13 : 3319994654
Total Pages : 266 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Materials Discovery and Design by : Turab Lookman

Download or read book Materials Discovery and Design written by Turab Lookman and published by Springer. This book was released on 2018-09-22 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the application of data science to materials problems are sketched. Computational and experimental facilities today generate vast amounts of data at an unprecedented rate. The book gives guidance to discover new knowledge that enables materials innovation to address grand challenges in energy, environment and security, the clearer link needed between the data from these facilities and the theory and underlying science. The role of inference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key to achieving the desired goals of real time analysis and feedback. Thus, the importance of this book lies in emphasizing that the full value of knowledge driven discovery using data can only be realized by integrating statistical and information sciences with materials science, which is increasingly dependent on high throughput and large scale computational and experimental data gathering efforts. This is especially the case as we enter a new era of big data in materials science with the planning of future experimental facilities such as the Linac Coherent Light Source at Stanford (LCLS-II), the European X-ray Free Electron Laser (EXFEL) and MaRIE (Matter Radiation in Extremes), the signature concept facility from Los Alamos National Laboratory. These facilities are expected to generate hundreds of terabytes to several petabytes of in situ spatially and temporally resolved data per sample. The questions that then arise include how we can learn from the data to accelerate the processing and analysis of reconstructed microstructure, rapidly map spatially resolved properties from high throughput data, devise diagnostics for pattern detection, and guide experiments towards desired targeted properties. The authors are an interdisciplinary group of leading experts who bring the excitement of the nascent and rapidly emerging field of materials informatics to the reader.

Machine Learning Meets Quantum Physics

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Publisher : Springer Nature
ISBN 13 : 3030402452
Total Pages : 473 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning Meets Quantum Physics by : Kristof T. Schütt

Download or read book Machine Learning Meets Quantum Physics written by Kristof T. Schütt and published by Springer Nature. This book was released on 2020-06-03 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.

Introduction to Reticular Chemistry

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Publisher : John Wiley & Sons
ISBN 13 : 3527821104
Total Pages : 742 pages
Book Rating : 4.5/5 (278 download)

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Book Synopsis Introduction to Reticular Chemistry by : Omar M. Yaghi

Download or read book Introduction to Reticular Chemistry written by Omar M. Yaghi and published by John Wiley & Sons. This book was released on 2019-03-22 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise introduction to the chemistry and design principles behind important metal-organic frameworks and related porous materials Reticular chemistry has been applied to synthesize new classes of porous materials that are successfully used for myraid applications in areas such as gas separation, catalysis, energy, and electronics. Introduction to Reticular Chemistry gives an unique overview of the principles of the chemistry behind metal-organic frameworks (MOFs), covalent organic frameworks (COFs), and zeolitic imidazolate frameworks (ZIFs). Written by one of the pioneers in the field, this book covers all important aspects of reticular chemistry, including design and synthesis, properties and characterization, as well as current and future applications Designed to be an accessible resource, the book is written in an easy-to-understand style. It includes an extensive bibliography, and offers figures and videos of crystal structures that are available as an electronic supplement. Introduction to Reticular Chemistry: -Describes the underlying principles and design elements for the synthesis of important metal-organic frameworks (MOFs) and related materials -Discusses both real-life and future applications in various fields, such as clean energy and water adsorption -Offers all graphic material on a companion website -Provides first-hand knowledge by Omar Yaghi, one of the pioneers in the field, and his team. Aimed at graduate students in chemistry, structural chemists, inorganic chemists, organic chemists, catalytic chemists, and others, Introduction to Reticular Chemistry is a groundbreaking book that explores the chemistry principles and applications of MOFs, COFs, and ZIFs.

Morphology and the Web of Grammar

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Publisher : Center for the Study of Language and Information Publica Tion
ISBN 13 :
Total Pages : 316 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis Morphology and the Web of Grammar by : C. Orhan Orgun

Download or read book Morphology and the Web of Grammar written by C. Orhan Orgun and published by Center for the Study of Language and Information Publica Tion. This book was released on 2005 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description

Computational Materials Discovery

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Publisher : Royal Society of Chemistry
ISBN 13 : 1782629610
Total Pages : 470 pages
Book Rating : 4.7/5 (826 download)

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Book Synopsis Computational Materials Discovery by : Artem Oganov

Download or read book Computational Materials Discovery written by Artem Oganov and published by Royal Society of Chemistry. This book was released on 2018-10-30 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique and timely book providing an overview of both the methodologies and applications of computational materials design.

Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0

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Publisher : Springer Nature
ISBN 13 : 3031563107
Total Pages : 291 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 by : D. Jude Hemanth

Download or read book Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 written by D. Jude Hemanth and published by Springer Nature. This book was released on with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Hands-On Mathematics for Deep Learning

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Publisher : Packt Publishing Ltd
ISBN 13 : 183864184X
Total Pages : 347 pages
Book Rating : 4.8/5 (386 download)

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Book Synopsis Hands-On Mathematics for Deep Learning by : Jay Dawani

Download or read book Hands-On Mathematics for Deep Learning written by Jay Dawani and published by Packt Publishing Ltd. This book was released on 2020-06-12 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, image, text, and sequence applicationsBook Description Most programmers and data scientists struggle with mathematics, having either overlooked or forgotten core mathematical concepts. This book uses Python libraries to help you understand the math required to build deep learning (DL) models. You'll begin by learning about core mathematical and modern computational techniques used to design and implement DL algorithms. This book will cover essential topics, such as linear algebra, eigenvalues and eigenvectors, the singular value decomposition concept, and gradient algorithms, to help you understand how to train deep neural networks. Later chapters focus on important neural networks, such as the linear neural network and multilayer perceptrons, with a primary focus on helping you learn how each model works. As you advance, you will delve into the math used for regularization, multi-layered DL, forward propagation, optimization, and backpropagation techniques to understand what it takes to build full-fledged DL models. Finally, you’ll explore CNN, recurrent neural network (RNN), and GAN models and their application. By the end of this book, you'll have built a strong foundation in neural networks and DL mathematical concepts, which will help you to confidently research and build custom models in DL. What you will learnUnderstand the key mathematical concepts for building neural network modelsDiscover core multivariable calculus conceptsImprove the performance of deep learning models using optimization techniquesCover optimization algorithms, from basic stochastic gradient descent (SGD) to the advanced Adam optimizerUnderstand computational graphs and their importance in DLExplore the backpropagation algorithm to reduce output errorCover DL algorithms such as convolutional neural networks (CNNs), sequence models, and generative adversarial networks (GANs)Who this book is for This book is for data scientists, machine learning developers, aspiring deep learning developers, or anyone who wants to understand the foundation of deep learning by learning the math behind it. Working knowledge of the Python programming language and machine learning basics is required.

Recent Advances in Sustainable Process Design and Optimization

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Publisher : World Scientific
ISBN 13 : 9814271950
Total Pages : 831 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Recent Advances in Sustainable Process Design and Optimization by : Dominic C. Y. Foo

Download or read book Recent Advances in Sustainable Process Design and Optimization written by Dominic C. Y. Foo and published by World Scientific. This book was released on 2012 with total page 831 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of the various recently developed techniques emphasizing better chemical processes and products, with state-of-the-art contributions by world-renowned leaders in process design and optimization. It covers various areas such as grass-roots design, retrofitting, continuous and batch processing, energy efficiency, separations, and pollution prevention, striking a balance between fundamental techniques and applications. The book also contains industrial applications and will serve as a good compilation of recent industrial experience for which the process design and optimization techniques were applied to enhance sustainability. Academic researchers and industrial practitioners will find this book useful as a review of systematic approaches and best practices in sustainable design and optimization of industrial processes. The book is accompanied by some electronic supplements (i.e., models and programs) for selected chapters.

Beyond the Molecular Frontier

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Publisher : National Academies Press
ISBN 13 : 0309168392
Total Pages : 238 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Beyond the Molecular Frontier by : National Research Council

Download or read book Beyond the Molecular Frontier written by National Research Council and published by National Academies Press. This book was released on 2003-03-19 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemistry and chemical engineering have changed significantly in the last decade. They have broadened their scopeâ€"into biology, nanotechnology, materials science, computation, and advanced methods of process systems engineering and controlâ€"so much that the programs in most chemistry and chemical engineering departments now barely resemble the classical notion of chemistry. Beyond the Molecular Frontier brings together research, discovery, and invention across the entire spectrum of the chemical sciencesâ€"from fundamental, molecular-level chemistry to large-scale chemical processing technology. This reflects the way the field has evolved, the synergy at universities between research and education in chemistry and chemical engineering, and the way chemists and chemical engineers work together in industry. The astonishing developments in science and engineering during the 20th century have made it possible to dream of new goals that might previously have been considered unthinkable. This book identifies the key opportunities and challenges for the chemical sciences, from basic research to societal needs and from terrorism defense to environmental protection, and it looks at the ways in which chemists and chemical engineers can work together to contribute to an improved future.

Machine Learning in Chemistry

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Publisher : Royal Society of Chemistry
ISBN 13 : 1788017897
Total Pages : 564 pages
Book Rating : 4.7/5 (88 download)

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Book Synopsis Machine Learning in Chemistry by : Hugh M. Cartwright

Download or read book Machine Learning in Chemistry written by Hugh M. Cartwright and published by Royal Society of Chemistry. This book was released on 2020-07-15 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.

Chemical Engineering Design

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Publisher : Elsevier
ISBN 13 : 0080966608
Total Pages : 1321 pages
Book Rating : 4.0/5 (89 download)

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Book Synopsis Chemical Engineering Design by : Gavin Towler

Download or read book Chemical Engineering Design written by Gavin Towler and published by Elsevier. This book was released on 2012-01-25 with total page 1321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemical Engineering Design, Second Edition, deals with the application of chemical engineering principles to the design of chemical processes and equipment. Revised throughout, this edition has been specifically developed for the U.S. market. It provides the latest US codes and standards, including API, ASME and ISA design codes and ANSI standards. It contains new discussions of conceptual plant design, flowsheet development, and revamp design; extended coverage of capital cost estimation, process costing, and economics; and new chapters on equipment selection, reactor design, and solids handling processes. A rigorous pedagogy assists learning, with detailed worked examples, end of chapter exercises, plus supporting data, and Excel spreadsheet calculations, plus over 150 Patent References for downloading from the companion website. Extensive instructor resources, including 1170 lecture slides and a fully worked solutions manual are available to adopting instructors. This text is designed for chemical and biochemical engineering students (senior undergraduate year, plus appropriate for capstone design courses where taken, plus graduates) and lecturers/tutors, and professionals in industry (chemical process, biochemical, pharmaceutical, petrochemical sectors). New to this edition: - Revised organization into Part I: Process Design, and Part II: Plant Design. The broad themes of Part I are flowsheet development, economic analysis, safety and environmental impact and optimization. Part II contains chapters on equipment design and selection that can be used as supplements to a lecture course or as essential references for students or practicing engineers working on design projects. - New discussion of conceptual plant design, flowsheet development and revamp design - Significantly increased coverage of capital cost estimation, process costing and economics - New chapters on equipment selection, reactor design and solids handling processes - New sections on fermentation, adsorption, membrane separations, ion exchange and chromatography - Increased coverage of batch processing, food, pharmaceutical and biological processes - All equipment chapters in Part II revised and updated with current information - Updated throughout for latest US codes and standards, including API, ASME and ISA design codes and ANSI standards - Additional worked examples and homework problems - The most complete and up to date coverage of equipment selection - 108 realistic commercial design projects from diverse industries - A rigorous pedagogy assists learning, with detailed worked examples, end of chapter exercises, plus supporting data and Excel spreadsheet calculations plus over 150 Patent References, for downloading from the companion website - Extensive instructor resources: 1170 lecture slides plus fully worked solutions manual available to adopting instructors

Handbook of Materials Modeling

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Publisher : Springer Science & Business Media
ISBN 13 : 1402032862
Total Pages : 2903 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Handbook of Materials Modeling by : Sidney Yip

Download or read book Handbook of Materials Modeling written by Sidney Yip and published by Springer Science & Business Media. This book was released on 2007-11-17 with total page 2903 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first reference of its kind in the rapidly emerging field of computational approachs to materials research, this is a compendium of perspective-providing and topical articles written to inform students and non-specialists of the current status and capabilities of modelling and simulation. From the standpoint of methodology, the development follows a multiscale approach with emphasis on electronic-structure, atomistic, and mesoscale methods, as well as mathematical analysis and rate processes. Basic models are treated across traditional disciplines, not only in the discussion of methods but also in chapters on crystal defects, microstructure, fluids, polymers and soft matter. Written by authors who are actively participating in the current development, this collection of 150 articles has the breadth and depth to be a major contributor toward defining the field of computational materials. In addition, there are 40 commentaries by highly respected researchers, presenting various views that should interest the future generations of the community. Subject Editors: Martin Bazant, MIT; Bruce Boghosian, Tufts University; Richard Catlow, Royal Institution; Long-Qing Chen, Pennsylvania State University; William Curtin, Brown University; Tomas Diaz de la Rubia, Lawrence Livermore National Laboratory; Nicolas Hadjiconstantinou, MIT; Mark F. Horstemeyer, Mississippi State University; Efthimios Kaxiras, Harvard University; L. Mahadevan, Harvard University; Dimitrios Maroudas, University of Massachusetts; Nicola Marzari, MIT; Horia Metiu, University of California Santa Barbara; Gregory C. Rutledge, MIT; David J. Srolovitz, Princeton University; Bernhardt L. Trout, MIT; Dieter Wolf, Argonne National Laboratory.

2018 IEEE Symposium on Security and Privacy

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Publisher :
ISBN 13 : 9781538643532
Total Pages : pages
Book Rating : 4.6/5 (435 download)

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Book Synopsis 2018 IEEE Symposium on Security and Privacy by : IEEE Symposium on Security and Privacy

Download or read book 2018 IEEE Symposium on Security and Privacy written by IEEE Symposium on Security and Privacy and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence for Materials Science

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Publisher : Springer Nature
ISBN 13 : 3030683109
Total Pages : 231 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Artificial Intelligence for Materials Science by : Yuan Cheng

Download or read book Artificial Intelligence for Materials Science written by Yuan Cheng and published by Springer Nature. This book was released on 2021-03-26 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers.