informatics for materials science and engineering data driven discovery for accelerated experimentation and application

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Informatics For Materials Science And Engineering

Author : Krishna Rajan
ISBN : 9780123946140
Genre : Technology & Engineering
File Size : 29. 11 MB
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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

Author : Turab Lookman
ISBN : 9783319238715
Genre : Technology & Engineering
File Size : 45. 6 MB
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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.

Hierarchical Materials Informatics

Author : Surya R. Kalidindi
ISBN : 9780124104556
Genre : Technology & Engineering
File Size : 49. 49 MB
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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)

Materials Science And Engineering

Author : Duane D. Johnson
ISBN : 9780128059449
Genre : Technology & Engineering
File Size : 54. 39 MB
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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.

Hierarchical Materials Informatics

Author : Surya R. Kalidindi
ISBN : 9780124104556
Genre : Technology & Engineering
File Size : 39. 31 MB
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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)

Materials Science And Engineering

Author : Krishna Rajan
ISBN : 9780128059319
Genre : Technology & Engineering
File Size : 62. 36 MB
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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.

Proceedings Of The 4th World Congress On Integrated Computational Materials Engineering Icme 2017

Author : Paul Mason
ISBN : 9783319578644
Genre : Technology & Engineering
File Size : 90. 44 MB
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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

Materials Informatics

Author : Krishna Rajan
ISBN : 0471756199
Genre : Technology & Engineering
File Size : 61. 56 MB
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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.

Computational Approaches To Materials Design Theoretical And Practical Aspects

Author : Datta, Shubhabrata
ISBN : 9781522502913
Genre : Technology & Engineering
File Size : 29. 72 MB
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The development of new and superior materials is beneficial within industrial settings, as well as a topic of academic interest. By using computational modeling techniques, the probable application and performance of these materials can be easily evaluated. Computational Approaches to Materials Design: Theoretical and Practical Aspects brings together empirical research, theoretical concepts, and the various approaches in the design and discovery of new materials. Highlighting optimization tools and soft computing methods, this publication is a comprehensive collection for researchers, both in academia and in industrial settings, and practitioners who are interested in the application of computational techniques in the field of materials engineering.

Big Data In Materials Research And Development

Author : National Research Council
ISBN : 9780309303828
Genre : Technology & Engineering
File Size : 47. 96 MB
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Big Data in Materials Research and Development is the summary of a workshop convened by the National Research Council Standing Committee on Defense Materials Manufacturing and Infrastructure in February 2014 to discuss the impact of big data on materials and manufacturing. The materials science community would benefit from appropriate access to data and metadata for materials development, processing, application development, and application life cycles. Currently, that access does not appear to be sufficiently widespread, and many workshop participants captured the constraints and identified potential improvements to enable broader access to materials and manufacturing data and metadata. This report discusses issues in defense materials, manufacturing and infrastructure, including data ownership and access; collaboration and exploitation of big data's capabilities; and maintenance of data.

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