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Informatics For Materials Science And Engineering Data Driven Discovery For Accelerated Experimentation And Application
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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
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.
Book Synopsis Materials Informatics by : Krishna Rajan
Download or read book Materials Informatics written by Krishna Rajan and published by Wiley-Interscience. This book was released on 2018-01-03 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Materials Informatics: Data-Driven Discovery in Materials Science outlines the value of adding an "informatics" dimension to the analysis of materials science phenomena, by processes which can permit one to gather and survey complex, multiscale information. Such informatics and combinatorial approaches have emerged as powerful tools in materials design and discovery, in much the same way that genomics and bioinformatics impacted the biological arena. Including topics like data mining and combinatorial experimentation, this book covers the current state of the field, and provides examples (via case studies) of the analysis of multivariate data on a wide array of materials systems.
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.
Book Synopsis Hierarchical Materials Informatics by : Surya R. Kalidindi
Download or read book Hierarchical Materials Informatics written by Surya R. Kalidindi and published by Elsevier. This book was released on 2015-08-06 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Custom design, manufacture, and deployment of new high performance materials for advanced technologies is critically dependent on the availability of invertible, high fidelity, structure-property-processing (SPP) linkages. Establishing these linkages presents a major challenge because of the need to cover unimaginably large dimensional spaces. Hierarchical Materials Informatics addresses objective, computationally efficient, mining of large ensembles of experimental and modeling datasets to extract this core materials knowledge. Furthermore, it aims to organize and present this high value knowledge in highly accessible forms to end users engaged in product design and design for manufacturing efforts. As such, this emerging field has a pivotal role in realizing the goals outlined in current strategic national initiatives such as the Materials Genome Initiative (MGI) and the Advanced Manufacturing Partnership (AMP). This book presents the foundational elements of this new discipline as it relates to the design, development, and deployment of hierarchical materials critical to advanced technologies. Addresses a critical gap in new materials research and development by presenting a rigorous statistical framework for the quantification of microstructure Contains several case studies illustrating the use of modern data analytic tools on microstructure datasets (both experimental and modeling)
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
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.
Book Synopsis Proceedings of the 4th World Congress on Integrated Computational Materials Engineering (ICME 2017) by : Paul Mason
Download or read book Proceedings of the 4th World Congress on Integrated Computational Materials Engineering (ICME 2017) written by Paul Mason and published by Springer. This book was released on 2017-04-27 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book represents a collection of papers presented at the 4th World Congress on Integrated Computational Materials Engineering (ICME 2017), a specialty conference organized by The Minerals, Metals & Materials Society (TMS). The contributions offer topics relevant to the global advancement of ICME as an engineering discipline. Topics covered include the following:ICME Success Stories and ApplicationsVerification, Validation, Uncertainty Quantification Issues and Gap AnalysisIntegration Framework and UsageAdditive ManufacturingPhase Field ModelingMicrostructure EvolutionICME Design Tools and ApplicationMechanical Performance Using Multi-Scale Modeling
Book Synopsis Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes) by :
Download or read book Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes) written by and published by World Scientific. This book was released on 2020-03-10 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances in instrument — driven data generation and analytics, establishing the links between the big data and predictive theories, and outlining the emerging field of data and physics-driven predictive and autonomous systems.
Book Synopsis The Fourth Paradigm by : Anthony J. G. Hey
Download or read book The Fourth Paradigm written by Anthony J. G. Hey and published by . This book was released on 2009 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foreword. A transformed scientific method. Earth and environment. Health and wellbeing. Scientific infrastructure. Scholarly communication.
Book Synopsis Dynamic Response of Advanced Ceramics by : Ghatu Subhash
Download or read book Dynamic Response of Advanced Ceramics written by Ghatu Subhash and published by John Wiley & Sons. This book was released on 2021-04-28 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic Response of Advanced Ceramics Discover fundamental concepts and recent advances in experimental, analytical, and computational research into the dynamic behavior of ceramics In Dynamic Response of Advanced Ceramics, an accomplished team of internationally renowned researchers delivers a comprehensive exploration of foundational and advanced concepts in experimental, analytical, and computational aspects of the dynamic behavior of advanced structural ceramics and transparent materials. The book discusses new techniques used for determination of dynamic hardness and dynamic fracture toughness, as well as edge-on-impact experiments for imaging evolving damage patterns at high impact velocities. The authors also include descriptions of the dynamic deformation behavior of icosahedral ceramics and the dynamic behavior of several transparent materials, like chemically strengthened glass and glass ceramics. The developments discussed within the book have applications in everything from high-speed machining to cutting, grinding, and blast protection. Readers will also benefit from a presentation of emerging trends and directions in research on this subject as well as current challenges in experimental and computational domains, including: An introduction to the history of ceramic materials and their dynamic behavior, including examples of material response to high-strain-rate loading An exploration of high-strain-rate experimental techniques, like 1D elastic stress-wave propagation techniques, shock waves, and impact testing Discussions of the static and dynamic responses of ceramics and the shock response of brittle solids An overview of deformation mechanisms during projectile impact on a confined ceramic, including damage evolution during the nonpenetration and penetration phases. Perfect for researchers, scientists, and engineers working on ballistic impact and shock response of brittle materials, Dynamic Response of Advanced Ceramics will also earn a place in the libraries of industry personnel studying impact-resistant solutions for a variety of applications.
Book Synopsis Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes by : Anand Balu Nellippallil
Download or read book Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes written by Anand Balu Nellippallil and published by Springer Nature. This book was released on 2020-06-13 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores systems-based, co-design, introducing a “Decision-Based, Co-Design” (DBCD) approach for the co-design of materials, products, and processes. In recent years there have been significant advances in modeling and simulation of material behavior, from the smallest atomic scale to the macro scale. However, the uncertainties associated with these approaches and models across different scales need to be addressed to enable decision-making resulting in designs that are robust, that is, relatively insensitive to uncertainties. An approach that facilitates co-design is needed across material, product design and manufacturing processes. This book describes a cloud-based platform to support decisions in the design of engineered systems (CB-PDSIDES), which feature an architecture that promotes co-design through the servitization of decision-making, knowledge capture and use templates that allow previous solutions to be reused. Placing the platform in the cloud aids mass collaboration and open innovation. A valuable reference resource reference on all areas related to the design of materials, products and processes, the book appeals to material scientists, design engineers and all those involved in the emerging interdisciplinary field of integrated computational materials engineering (ICME).
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.
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.
Book Synopsis Reviews in Computational Chemistry by : Abby L. Parrill
Download or read book Reviews in Computational Chemistry written by Abby L. Parrill and published by John Wiley & Sons. This book was released on 2016-03-09 with total page 480 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
Book Synopsis Materials Science and Engineering by : Krishna Rajan
Download or read book Materials Science and Engineering written by Krishna Rajan 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: Studying structure–property relationships is an accepted paradigm in materials science, yet these relationships are often not linear and the challenge is to seek patterns among multiple length and time scales. There is rarely a single multiscale theory or experiment that can meaningfully and accurately capture such information. In this chapter we introduce the rationale as to why we need informatics by briefly summarizing the challenges of information complexity one has to deal with in material science, in order to systematically establish structure–property–processing relationships. Some of the concepts and topics to be covered in this book are introduced, including information networks, data mining, databases, and combinatorial experiments to mention a few. The value of “materials informatics” lies in its ability to permit one to survey complex, multiscale information in a high-throughput, statistically robust and yet physically meaningful manner.
Book Synopsis Properties and Characterization of Modern Materials by : Andreas Öchsner
Download or read book Properties and Characterization of Modern Materials written by Andreas Öchsner and published by Springer. This book was released on 2016-07-30 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on robust characterization and prediction methods for materials in technical applications as well as the materials’ safety features during operation. In particular, it presents methods for reliably predicting material properties, an aspect that is becoming increasingly important as engineering materials are pushed closer and closer to their limits to boost the performance of machines and structures. To increase their engineering value, components are now designed under the consideration of their multiphysical properties and functions, which requires much more intensive investigation and characterization of these materials. The materials covered in this monograph range from metal-based groups such as lightweight alloys, to advanced high-strength steels and modern titanium alloys. Furthermore, a wide range of polymers and composite materials (e.g. with micro- and nanoparticles or fibres) is covered. The book explores methods for property prediction from classical mechanical characterization-related fields of application, for example, from wear, creep, fatigue and crack growth, to specific surface properties, to dielectric and electrochemical values. As in all fields of modern engineering, the process is often accompanied by numerical simulation and optimization.
