Information Science for Materials Discovery and Design (Paperback, Softcover reprint of the original 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Springer Series in Materials Science, 225
Release date:	March 2019
First published:	2016
Editors:	Turab Lookman • Francis J. Alexander • Krishna Rajan
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	307
Edition:	Softcover reprint of the original 1st ed. 2016
ISBN-13:	978-3-319-79541-6
Categories:	Books > Professional & Technical > Technology: general issues > Nanotechnology Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics Books > Computing & IT > Applications of computing > Databases > Data mining Books > Professional & Technical > Mechanical engineering & materials > Materials science > Testing of materials > General
LSN:	3-319-79541-4
Barcode:	9783319795416

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