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100%: Turab Lookman; Stephan Eidenbenz; Frank Alexander; Cris Barnes: Materials Discovery and Design (ISBN: 9783319994659) Springer Nature, in Englisch, auch als eBook.
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40%: Herausgeber: Turab Lookman, Herausgeber: Francis J. Alexander, Herausgeber: Krishna Rajan: Information Science for Materials Discovery and Design (Springer Series in Materials Science) (ISBN: 9783319795416) 2017, Springer, in Englisch, Taschenbuch.
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Materials Discovery and Design - 3 Angebote vergleichen
Bester Preis: Fr. 90.90 (€ 92.88)¹ (vom 01.08.2018)1
Materials Discovery and Design
~EN NW EB DL
ISBN: 9783319994659 bzw. 3319994654, vermutlich in Englisch, Springer Nature, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, Lagernd, zzgl. Versandkosten.
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. eBook.
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. eBook.
2
Information Science for Materials Discovery and Design (Springer Series in Materials Science) (2017)
EN PB NW RP
ISBN: 9783319795416 bzw. 3319795414, in Englisch, 307 Seiten, Springer, Taschenbuch, neu, Nachdruck.
Lieferung aus: Deutschland, Noch nicht erschienen. Versandkostenfrei.
Von Händler/Antiquariat, Amazon.de.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Von Händler/Antiquariat, Amazon.de.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
3
Materials Discovery and Design
DE NW EB
ISBN: 9783319994659 bzw. 3319994654, in Deutsch, Springer Nature, neu, E-Book.
Lieferung aus: Vereinigtes Königreich Grossbritannien und Nordirland, Lagernd.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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