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Author: Artem Oganov
Publisher: Royal Society of Chemistry
ISBN: 1782629610
Category : Science
Languages : en
Pages : 470
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Book Description
A unique and timely book providing an overview of both the methodologies and applications of computational materials design.
Author: Artem Oganov
Publisher: Royal Society of Chemistry
ISBN: 1782629610
Category : Science
Languages : en
Pages : 470
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Book Description
A unique and timely book providing an overview of both the methodologies and applications of computational materials design.
Author: Richard LeSar
Publisher: Cambridge University Press
ISBN: 1107328144
Category : Technology & Engineering
Languages : en
Pages : 429
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Book Description
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.
Author: Turab Lookman
Publisher: Springer
ISBN: 331923871X
Category : Technology & Engineering
Languages : en
Pages : 316
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Book Description
This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop for materials design) to involve iteratively learning from experiments and calculations to develop materials with optimum properties. Such a loop requires the elements of incorporating domain materials knowledge, a database of descriptors (the genes), a surrogate or statistical model developed to predict a given property with uncertainties, performing adaptive experimental design to guide the next experiment or calculation and aspects of high throughput calculations as well as experiments. The book is about manufacturing with the aim to halving the time to discover and design new materials. Accelerating discovery relies on using large databases, computation, and mathematics in the material sciences in a manner similar to the way used to in the Human Genome Initiative. Novel approaches are therefore called to explore the enormous phase space presented by complex materials and processes. To achieve the desired performance gains, a predictive capability is needed to guide experiments and computations in the most fruitful directions by reducing not successful trials. Despite advances in computation and experimental techniques, generating vast arrays of data; without a clear way of linkage to models, the full value of data driven discovery cannot be realized. Hence, along with experimental, theoretical and computational materials science, we need to add a “fourth leg’’ to our toolkit to make the “Materials Genome'' a reality, the science of Materials Informatics.
Author: Sadasivan Shankar
Publisher: Springer Nature
ISBN: 3030187780
Category : Technology & Engineering
Languages : en
Pages : 1344
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Book Description
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.
Author: Shubham Tayal
Publisher: CRC Press
ISBN: 1000459837
Category : Science
Languages : en
Pages : 258
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Book Description
Advanced materials are essential for economic security and human well-being, with applications in industries aimed at addressing challenges in clean energy, national security, and human welfare. Yet, it can take years to move a material to the market after its initial discovery. Computational techniques have accelerated the exploration and development of materials, offering the chance to move new materials to the market quickly. Computational Technologies in Materials Science addresses topics related to AI, machine learning, deep learning, and cloud computing in materials science. It explores characterization and fabrication of materials, machine-learning-based models, and computational intelligence for the synthesis and identification of materials. This book • Covers material testing and development using computational intelligence • Highlights the technologies to integrate computational intelligence and materials science • Details case studies and detailed applications • Investigates challenges in developing and using computational intelligence in materials science • Analyzes historic changes that are taking place in designing materials. This book encourages material researchers and academics to develop novel theories and sustainable computational techniques and explores the potential for computational intelligence to replace traditional materials research.
Author: A.M. Ovrutsky
Publisher: Elsevier
ISBN: 0124202071
Category : Computers
Languages : en
Pages : 389
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Book Description
Computational Materials Science provides the theoretical basis necessary for understanding atomic surface phenomena and processes of phase transitions, especially crystallization, is given. The most important information concerning computer simulation by different methods and simulation techniques for modeling of physical systems is also presented. A number of results are discussed regarding modern studies of surface processes during crystallization. There is sufficiently full information on experiments, theory, and simulations concerning the surface roughening transition, kinetic roughening, nucleation kinetics, stability of crystal shapes, thin film formation, imperfect structure of small crystals, size dependent growth velocity, distribution coefficient at growth from alloy melts, superstructure ordering in the intermetallic compound. Computational experiments described in the last chapter allow visualization of the course of many processes and better understanding of many key problems in Materials Science. There is a set of practical steps concerning computational procedures presented. Open access to executable files in the book make it possible for everyone to understand better phenomena and processes described in the book. - Valuable reference book, but also helpful as a supplement to courses - Computer programs available to supplement examples - Presents several new methods of computational materials science and clearly summarizes previous methods and results
Author: Yuan Cheng
Publisher: Springer Nature
ISBN: 3030683109
Category : Technology & Engineering
Languages : en
Pages : 231
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Book Description
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.
Author: Shubhabrata Datta
Publisher: Engineering Science Reference
ISBN: 9781522502906
Category : Materials
Languages : en
Pages : 0
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Book Description
Brings together empirical research, theoretical concepts, and the various approaches in the design and discovery of new materials. Thois volume highlights optimization tools and soft computing methods, and is ideal for researchers, both in academia and in industrial settings, and practitioners who are interested in the application of computational techniques in materials engineering.
Author: Olexandr Isayev
Publisher: John Wiley & Sons
ISBN: 3527341218
Category : Technology & Engineering
Languages : en
Pages : 304
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Book Description
Provides everything readers need to know for applying the power of informatics to materials science There is a tremendous interest in materials informatics and application of data mining to materials science. This book is a one-stop guide to the latest advances in these emerging fields. Bridging the gap between materials science and informatics, it introduces readers to up-to-date data mining and machine learning methods. It also provides an overview of state-of-the-art software and tools. Case studies illustrate the power of materials informatics in guiding the experimental discovery of new materials. Materials Informatics: Methods, Tools and Applications is presented in two parts?Methodological Aspects of Materials Informatics and Practical Aspects and Applications. The first part focuses on developments in software, databases, and high-throughput computational activities. Chapter topics include open quantum materials databases; the ICSD database; open crystallography databases; and more. The second addresses the latest developments in data mining and machine learning for materials science. Its chapters cover genetic algorithms and crystal structure prediction; MQSPR modeling in materials informatics; prediction of materials properties; amongst others. -Bridges the gap between materials science and informatics -Covers all the known methodologies and applications of materials informatics -Presents case studies that illustrate the power of materials informatics in guiding the experimental quest for new materials -Examines the state-of-the-art software and tools being used today Materials Informatics: Methods, Tools and Applications is a must-have resource for materials scientists, chemists, and engineers interested in the methods of materials informatics.
Author: Turab Lookman
Publisher: Springer
ISBN: 3319994654
Category : Science
Languages : en
Pages : 266
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Book Description
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.
