Accelerated Materials Discovery

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Author :
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110738082
Total Pages : 215 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Accelerated Materials Discovery by : Phil De Luna

Download or read book Accelerated Materials Discovery written by Phil De Luna and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-02-21 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Typical timelines to go from discovery to impact in the advanced materials sector are between 10 to 30 years. Advances in robotics and artificial intelligence are poised to accelerate the discovery and development of new materials dramatically. This book is a primer for any materials scientist looking to future-proof their careers and get ahead of the disruption that artificial intelligence and robotic automation is just starting to unleash. It is meant to be an overview of how we can use these disruptive technologies to augment and supercharge our abilities to discover new materials that will solve world’s biggest challenges. Written by world leading experts on accelerated materials discovery from academia (UC Berkeley, Caltech, UBC, Cornell, etc.), industry (Toyota Research Institute, Citrine Informatics) and national labs (National Research Council of Canada, Lawrence Berkeley National Labs).

Informatics for Materials Science and Engineering: Data-Driven Discovery for Accelerated Experimentation and Application

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Author :
Publisher : Butterworth-Heinemann
ISBN 13 : 9780128101216
Total Pages : 542 pages
Book Rating : 4.1/5 (12 download)

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Book Synopsis Informatics for Materials Science and Engineering: Data-Driven Discovery for Accelerated Experimentation and Application by : Krishna Rajan

Download or read book Informatics for Materials Science and Engineering: Data-Driven Discovery for Accelerated Experimentation and Application written by Krishna Rajan and published by Butterworth-Heinemann. This book was released on 2017-11-13 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Materials informatics: a hot topic area in materials science, aims to combine traditionally bio-led informatics with computational methodologies, supporting more efficient research by identifying strategies for time- and cost-effective analysis. The discovery and maturation of new materials has been outpaced by the thicket of data created by new combinatorial and high throughput analytical techniques. The elaboration of this "quantitative avalanche" and the resulting complex, multi-factor analyses required to understand it means that interest, investment, and research are revisiting informatics approaches as a solution. This work, from Krishna Rajan, the leading expert of the informatics approach to materials, seeks to break down the barriers between data management, quality standards, data mining, exchange, and storage and analysis, as a means of accelerating scientific research in materials science. This solutions-based reference synthesizes foundational physical, statistical, and mathematical content with emerging experimental and real-world applications, for interdisciplinary researchers and those new to the field. Identifies and analyzes interdisciplinary strategies (including combinatorial and high throughput approaches) that accelerate materials development cycle times and reduces associated costs Mathematical and computational analysis aids formulation of new structure-property correlations among large, heterogeneous, and distributed data sets Practical examples, computational tools, and software analysis benefits rapid identification of critical data and analysis of theoretical needs for future problems "

Information Science for Materials Discovery and Design

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Author :
Publisher : Springer
ISBN 13 : 331923871X
Total Pages : 307 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Information Science for Materials Discovery and Design by : Turab Lookman

Download or read book Information Science for Materials Discovery and Design written by Turab Lookman and published by Springer. This book was released on 2015-12-12 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence for Materials Science

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Author :
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.

Accelerated Materials Discovery

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Author :
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110733250
Total Pages : 235 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Accelerated Materials Discovery by : Phil De Luna

Download or read book Accelerated Materials Discovery written by Phil De Luna and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-02-21 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Typical timelines to go from discovery to impact in the advanced materials sector are between 10 to 30 years. Advances in robotics and artificial intelligence are poised to accelerate the discovery and development of new materials dramatically. This book is a primer for any materials scientist looking to future-proof their careers and get ahead of the disruption that artificial intelligence and robotic automation is just starting to unleash. It is meant to be an overview of how we can use these disruptive technologies to augment and supercharge our abilities to discover new materials that will solve world’s biggest challenges. Written by world leading experts on accelerated materials discovery from academia (UC Berkeley, Caltech, UBC, Cornell, etc.), industry (Toyota Research Institute, Citrine Informatics) and national labs (National Research Council of Canada, Lawrence Berkeley National Labs).

Materials Discovery and Design

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Author :
Publisher : Springer
ISBN 13 : 3319994654
Total Pages : 256 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 256 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.

Computational Materials Discovery

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Author :
Publisher : Royal Society of Chemistry
ISBN 13 : 1782629610
Total Pages : 456 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 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Materials Informatics

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 3527341218
Total Pages : 304 pages
Book Rating : 4.5/5 (273 download)

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Book Synopsis Materials Informatics by : Olexandr Isayev

Download or read book Materials Informatics written by Olexandr Isayev and published by John Wiley & Sons. This book was released on 2019-12-04 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Knowledge Guided Machine Learning

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Author :
Publisher : CRC Press
ISBN 13 : 1000598136
Total Pages : 520 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Knowledge Guided Machine Learning by : Anuj Karpatne

Download or read book Knowledge Guided Machine Learning written by Anuj Karpatne and published by CRC Press. This book was released on 2022-08-15 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML

Materials Science and Engineering

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Author :
Publisher : Elsevier Inc. Chapters
ISBN 13 : 0128059443
Total Pages : 542 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Materials Science and Engineering by : Duane D. Johnson

Download or read book Materials Science and Engineering written by Duane D. Johnson and published by Elsevier Inc. Chapters. This book was released on 2013-07-10 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: We exemplify and propose extending the use of genetic programs (GPs) – a genetic algorithm (GA) that evolves computer programs via mechanisms similar to genetics and natural selection – to symbolically regress key functional relationships between materials data, especially from electronic structure. GPs can extract structure–property relations or enable simulations across multiple scales of time and/or length. Uniquely, GP-based regression permits “data discovery” – finding relevant data and/or extracting correlations (data reduction/data mining) – in contrast to searching for what you know, or you think you know (intuition). First, catalysis-related materials correlations are discussed, where simple electronic-structure-based rules are revealed using well-developed intuition, and then, after introducing the concepts, GP regression is used to obtain (i) a constitutive relation between flow stress and strain rate in aluminum, and (ii) multi-time-scale kinetics for surface alloys. We close with some outlook for a range of applications (materials discovery, excited-state chemistry, and multiscaling) that could rely primarily on density functional theory results.

Quantum Chemistry in the Age of Machine Learning

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Author :
Publisher : Elsevier
ISBN 13 : 0323886043
Total Pages : 702 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Quantum Chemistry in the Age of Machine Learning by : Pavlo O. Dral

Download or read book Quantum Chemistry in the Age of Machine Learning written by Pavlo O. Dral and published by Elsevier. This book was released on 2022-09-16 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum chemistry is simulating atomistic systems according to the laws of quantum mechanics, and such simulations are essential for our understanding of the world and for technological progress. Machine learning revolutionizes quantum chemistry by increasing simulation speed and accuracy and obtaining new insights. However, for nonspecialists, learning about this vast field is a formidable challenge. Quantum Chemistry in the Age of Machine Learning covers this exciting field in detail, ranging from basic concepts to comprehensive methodological details to providing detailed codes and hands-on tutorials. Such an approach helps readers get a quick overview of existing techniques and provides an opportunity to learn the intricacies and inner workings of state-of-the-art methods. The book describes the underlying concepts of machine learning and quantum chemistry, machine learning potentials and learning of other quantum chemical properties, machine learning-improved quantum chemical methods, analysis of Big Data from simulations, and materials design with machine learning. Drawing on the expertise of a team of specialist contributors, this book serves as a valuable guide for both aspiring beginners and specialists in this exciting field. Compiles advances of machine learning in quantum chemistry across different areas into a single resource Provides insights into the underlying concepts of machine learning techniques that are relevant to quantum chemistry Describes, in detail, the current state-of-the-art machine learning-based methods in quantum chemistry

Neither Physics nor Chemistry

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Author :
Publisher : MIT Press
ISBN 13 : 0262297876
Total Pages : 367 pages
Book Rating : 4.2/5 (622 download)

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Book Synopsis Neither Physics nor Chemistry by : Kostas Gavroglu

Download or read book Neither Physics nor Chemistry written by Kostas Gavroglu and published by MIT Press. This book was released on 2011-10-07 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: The evolution of a discipline at the intersection of physics, chemistry, and mathematics. Quantum chemistry—a discipline that is not quite physics, not quite chemistry, and not quite applied mathematics—emerged as a field of study in the 1920s. It was referred to by such terms as mathematical chemistry, subatomic theoretical chemistry, molecular quantum mechanics, and chemical physics until the community agreed on the designation of quantum chemistry. In Neither Physics Nor Chemistry, Kostas Gavroglu and Ana Simões examine the evolution of quantum chemistry into an autonomous discipline, tracing its development from the publication of early papers in the 1920s to the dramatic changes brought about by the use of computers in the 1970s. The authors focus on the culture that emerged from the creative synthesis of the various traditions of chemistry, physics, and mathematics. They examine the concepts, practices, languages, and institutions of this new culture as well as the people who established it, from such pioneers as Walter Heitler and Fritz London, Linus Pauling, and Robert Sanderson Mulliken, to later figures including Charles Alfred Coulson, Raymond Daudel, and Per-Olov Löwdin. Throughout, the authors emphasize six themes: epistemic aspects and the dilemmas caused by multiple approaches; social issues, including academic politics, the impact of textbooks, and the forging of alliances; the contingencies that arose at every stage of the developments in quantum chemistry; the changes in the field when computers were available to perform the extraordinarily cumbersome calculations required; issues in the philosophy of science; and different styles of reasoning.

Nanoinformatics

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Author :
Publisher : Springer
ISBN 13 : 9811076170
Total Pages : 298 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Nanoinformatics by : Isao Tanaka

Download or read book Nanoinformatics written by Isao Tanaka and published by Springer. This book was released on 2018-01-15 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering.

Materials Science and Engineering: Concepts, Methodologies, Tools, and Applications

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Author :
Publisher : IGI Global
ISBN 13 : 1522517995
Total Pages : 1804 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Materials Science and Engineering: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Materials Science and Engineering: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2017-01-11 with total page 1804 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design and study of materials is a pivotal component to new discoveries in the various fields of science and technology. By better understanding the components and structures of materials, researchers can increase its applications across different industries. Materials Science and Engineering: Concepts, Methodologies, Tools, and Applications is a compendium of the latest academic material on investigations, technologies, and techniques pertaining to analyzing the synthesis and design of new materials. Through its broad and extensive coverage on a variety of crucial topics, such as nanomaterials, biomaterials, and relevant computational methods, this multi-volume work is an essential reference source for engineers, academics, researchers, students, professionals, and practitioners seeking innovative perspectives in the field of materials science and engineering.

Informatics for Materials Science and Engineering

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Author :
Publisher : Butterworth-Heinemann
ISBN 13 : 012394614X
Total Pages : 542 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis Informatics for Materials Science and Engineering by : Krishna Rajan

Download or read book Informatics for Materials Science and Engineering written by Krishna Rajan and published by Butterworth-Heinemann. This book was released on 2013-07-10 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Materials informatics: a ‘hot topic’ area in materials science, aims to combine traditionally bio-led informatics with computational methodologies, supporting more efficient research by identifying strategies for time- and cost-effective analysis. The discovery and maturation of new materials has been outpaced by the thicket of data created by new combinatorial and high throughput analytical techniques. The elaboration of this "quantitative avalanche"—and the resulting complex, multi-factor analyses required to understand it—means that interest, investment, and research are revisiting informatics approaches as a solution. This work, from Krishna Rajan, the leading expert of the informatics approach to materials, seeks to break down the barriers between data management, quality standards, data mining, exchange, and storage and analysis, as a means of accelerating scientific research in materials science. This solutions-based reference synthesizes foundational physical, statistical, and mathematical content with emerging experimental and real-world applications, for interdisciplinary researchers and those new to the field. Identifies and analyzes interdisciplinary strategies (including combinatorial and high throughput approaches) that accelerate materials development cycle times and reduces associated costs Mathematical and computational analysis aids formulation of new structure-property correlations among large, heterogeneous, and distributed data sets Practical examples, computational tools, and software analysis benefits rapid identification of critical data and analysis of theoretical needs for future problems

Computational Technologies in Materials Science

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Author :
Publisher : CRC Press
ISBN 13 : 1000459748
Total Pages : 251 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Computational Technologies in Materials Science by : Shubham Tayal

Download or read book Computational Technologies in Materials Science written by Shubham Tayal and published by CRC Press. This book was released on 2021-10-06 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Covers material testing and development using computational intelligence • Highlights the technologies to integrate computational intelligence and materials sciences • Discusses how computational tools can generate new materials with advanced applications • 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 of materials

Reviews in Computational Chemistry, Volume 29

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119103932
Total Pages : 486 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Reviews in Computational Chemistry, Volume 29 by : Abby L. Parrill

Download or read book Reviews in Computational Chemistry, Volume 29 written by Abby L. Parrill and published by John Wiley & Sons. This book was released on 2016-04-11 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on molecular modeling, such as computer-assisted molecular design (CAMD), quantum chemistry, molecular mechanics and dynamics, and quantitative structure-activity relationships (QSAR). This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. Topics in Volume 29 include: Noncovalent Interactions in Density-Functional Theory Long-Range Inter-Particle Interactions: Insights from Molecular Quantum Electrodynamics (QED) Theory Efficient Transition-State Modeling using Molecular Mechanics Force Fields for the Everyday Chemist Machine Learning in Materials Science: Recent Progress and Emerging Applications Discovering New Materials via a priori Crystal Structure Prediction Introduction to Maximally Localized Wannier Functions Methods for a Rapid and Automated Description of Proteins: Protein Structure, Protein Similarity, and Protein Folding