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Computational Materials Design

Author: Tetsuya Saito
Publisher: Springer Science & Business Media
ISBN: 3662039230
Size: 52.95 MB
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This book consists of ten chapters which outline a wide range of technologies from first-principle calculations to continuum mechanics, with applications to materials design and development. Written with a clear exposition, this book will be invaluable for engineers who want to learn about the modern technologies and techniques utilized in materials design.

Information Science For Materials Discovery And Design

Author: Turab Lookman
Publisher: Springer
ISBN: 331923871X
Size: 78.12 MB
Format: PDF, Mobi
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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.

Multiscale Paradigms In Integrated Computational Materials Science And Engineering

Author: Pierre A. Deymier
Publisher: Springer
ISBN: 3319245295
Size: 72.95 MB
Format: PDF, Mobi
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This book presents cutting-edge concepts, paradigms, and research highlights in the field of computational materials science and engineering, and provides a fresh, up-to-date perspective on solving present and future materials challenges. The chapters are written by not only pioneers in the fields of computational materials chemistry and materials science, but also experts in multi-scale modeling and simulation as applied to materials engineering. Pedagogical introductions to the different topics and continuity between the chapters are provided to ensure the appeal to a broad audience and to address the applicability of integrated computational materials science and engineering for solving real-world problems.

Computational Materials Science

Author: Kaoru Ohno
Publisher: Springer Science & Business Media
ISBN: 9783540639619
Size: 41.73 MB
Format: PDF, Kindle
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This book introduces new theoretical techniques in materials research. With the computer power now available, it is possible to use numerical techniques to study various physical and chemical properties of complex materials from first principles. Some typical examples are presented and all the necessary equations and plots are included so that readers can fully understand the details. This book offers the materials scientist access to, and an understanding of the modern development of molecular dynamics and Monte Carlo simulation. It will also be of interest to physicists and chemists engaged in materials research.

Computational Materials Science

Author: Wofram Hergert
Publisher: Springer Science & Business Media
ISBN: 9783540210511
Size: 46.55 MB
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Computational Physics is now a discipline in its own right, comparable with theoretical and experimental physics. Computational Materials Science concentrates on the calculation of materials properties starting from microscopic theories. It has become a powerful tool in industrial research for designing new materials, modifying materials properties and optimizing chemical processes. This book focusses on the application of computational methods in new fields of research, such as nanotechnology, spintronics and photonics, which will provide the foundation for important technological advances in the future. Methods such as electronic structure calculations, molecular dynamics simulations and beyond are presented, the discussion extending from the basics to the latest applications.

Bayesian Optimization For Materials Science

Author: Daniel Packwood
Publisher: Springer
ISBN: 9811067813
Size: 76.27 MB
Format: PDF, Kindle
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This book provides a short and concise introduction to Bayesian optimization specifically for experimental and computational materials scientists. After explaining the basic idea behind Bayesian optimization and some applications to materials science in Chapter 1, the mathematical theory of Bayesian optimization is outlined in Chapter 2. Finally, Chapter 3 discusses an application of Bayesian optimization to a complicated structure optimization problem in computational surface science.Bayesian optimization is a promising global optimization technique that originates in the field of machine learning and is starting to gain attention in materials science. For the purpose of materials design, Bayesian optimization can be used to predict new materials with novel properties without extensive screening of candidate materials. For the purpose of computational materials science, Bayesian optimization can be incorporated into first-principles calculations to perform efficient, global structure optimizations. While research in these directions has been reported in high-profile journals, until now there has been no textbook aimed specifically at materials scientists who wish to incorporate Bayesian optimization into their own research. This book will be accessible to researchers and students in materials science who have a basic background in calculus and linear algebra.

Recent Trends In Physics Of Material Science And Technology

Author: Ford Lumban Gaol
Publisher: Springer
ISBN: 9812871284
Size: 67.56 MB
Format: PDF, ePub, Docs
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This book discusses in detail the recent trends in Computational Physics, Nano-physics and Devices Technology. Numerous modern devices with very high accuracy, are explored In conditions such as longevity and extended possibilities to work in wide temperature and pressure ranges, aggressive media, etc. This edited volume presents 32 selected papers of the 2013 International Conference on Science & Engineering in Mathematics, Chemistry and Physics. The book is divided into three scientific Sections: (i) Computational Physics, (ii) Nanophysics and Technology, (iii) Devices and Systems and is addressed to Professors, post-graduate students, scientists and engineers taking part in R&D of nano-materials, ferro-piezoelectrics, computational Physics and devices system, and also different devices based on broad applications in different areas of modern science and technology.

Numerical Modeling In Materials Science And Engineering

Author: Michel Rappaz
Publisher: Springer Science & Business Media
ISBN: 3642118216
Size: 30.49 MB
Format: PDF, ePub, Docs
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Computing application to materials science is one of the fastest-growing research areas. This book introduces the concepts and methodologies related to the modeling of the complex phenomena occurring in materials processing. It is intended for undergraduate and graduate students in materials science and engineering, mechanical engineering and physics, and for engineering professionals or researchers.

Computational Materials Design

Author: Tetsuya Saito
Publisher: Springer Science & Business Media
ISBN: 3662039230
Size: 41.36 MB
Format: PDF, Mobi
View: 7457
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This book consists of ten chapters which outline a wide range of technologies from first-principle calculations to continuum mechanics, with applications to materials design and development. Written with a clear exposition, this book will be invaluable for engineers who want to learn about the modern technologies and techniques utilized in materials design.

Computational Neuroscience

Author: Hanspeter Mallot
Publisher: Springer Science & Business Media
ISBN: 3319008617
Size: 76.17 MB
Format: PDF
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Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.