9783319238708 - information science for materials discovery and design: 225 (springer series in materials science, 225) (14 resultados)
Idioma: Inglés
Editorial: Springer, 2015
Serie: Libro 136 de 233 - Springer Series in Materials Science
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Condición: Very Good. Text block firm and clean, binding unblemished, boards straight, no highlights or underlining. Well packaged and promptly shipped from California. Partnered with Friends of the Library since 2010.
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Editorial: Springer, 2015
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Editorial: Springer International Publishing AG, CH, 2015
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Hardback. Condición: New. 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 wi…th 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'' toour toolkit to make the "Materials Genome'' a reality, the science of Materials Informatics.
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Serie: Libro 136 de 233 - Springer Series in Materials Science
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Idioma: Inglés
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Hardback. Condición: New. 1st ed. 2016.
Idioma: Inglés
Editorial: Springer, 2015
Serie: Libro 136 de 233 - Springer Series in Materials Science
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Condición: New. pp. 340.
Idioma: Inglés
Editorial: Springer International Publishing, Springer International Publishing, 2015
Serie: Libro 136 de 233 - Springer Series in Materials Science
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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'' toour toolkit to make the 'Materials Genome'' a reality, the science of Materials Informatics.
Information Science for Materials Discovery and Design
Lookman, Turab (Edited by)/ Alexander, Francis J. (Edited by)/ Rajan, Krishna (Edited by)
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Editorial: Springer, 2015
Serie: Libro 136 de 233 - Springer Series in Materials Science
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Hardcover. Condición: Brand New. 328 pages. 9.25x6.25x0.75 inches. In Stock.
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Editorial: Springer, 2015
Serie: Libro 136 de 233 - Springer Series in Materials Science
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Condición: new. Questo è un articolo print on demand.
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Editorial: Springer International Publishing, 2015
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. One of the first books on materials discovery strategyEmphasizes the paradigm of codesignBrings together diverse expertise to improve the model for materials discoveryThis book deals with an information-driv…en approach to plan ma.
Idioma: Inglés
Editorial: Springer International Publishing, Springer Nature Switzerland Dez 2015, 2015
Serie: Libro 136 de 233 - Springer Series in Materials Science
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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, combinatoria…l 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'' toour toolkit to make the 'Materials Genome'' a reality, the science of Materials Informatics. 328 pp. Englisch.
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Serie: Libro 136 de 233 - Springer Series in Materials Science
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Condición: New. Print on Demand pp. 340.
Idioma: Inglés
Editorial: Springer International Publishing, Springer International Publishing Dez 2015, 2015
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 246,09
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 ex…periments 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¿¿ toour toolkit to make the ¿Materials Genome'' a reality, the science of Materials Informatics.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 328 pp. Englisch.
Idioma: Inglés
Editorial: Springer, 2015
Serie: Libro 136 de 233 - Springer Series in Materials Science
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. PRINT ON DEMAND pp. 340.
