9783319994642 - materials discovery and design: by means of data science and optimal learning (springer series in materials science, 280, band 280) (4 Ergebnisse)
Materials Discovery and Design: By Means of Data Science and Optimal Learning (Springer Series in Materials Science, 280, Band 280) [Hardcover] Lookman, Turab; Eidenbenz, Stephan; Alexander, Frank and Barnes, Cris
Lookman, Turab; Eidenbenz, Stephan; Alexander, Frank; Barnes, Cris
Sprache: Englisch
Verlag: Springer, 2018
Serie: Buch 189 von 233 - Springer Series in Materials Science
- Hardcover
- Erstausgabe
Anbieter: SpringBooks, Berlin, DeutschlandSpringBooks
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EUR 84,68
EUR 39,90 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Hardcover. Zustand: As New. 1. Auflage. from Germany, will be dispatched immediately.
Sprache: Englisch
Verlag: Springer, 2018
Serie: Buch 189 von 233 - Springer Series in Materials Science
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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EUR 178,07
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Zustand: New. In.
Sprache: Englisch
Verlag: Springer, 2018
Serie: Buch 189 von 233 - Springer Series in Materials Science
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 185,68
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 questi…ons 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 ofinference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key toachieving 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 ofin situspatially 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.
Sprache: Englisch
Verlag: Springer Verlag, 2018
Serie: Buch 189 von 233 - Springer Series in Materials Science
- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
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EUR 277,00
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Hardcover. Zustand: Brand New. 256 pages. 9.50x6.50x0.80 inches. In Stock.
