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Materials discovery and design : by means of data science and optimal learning

Author: Turab Lookman; Stephan Eidenbenz; Frank Alexander; Cris Barnes
Publisher: Cham : Springer, 2018.
Series: Springer series in materials science, v. 280.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Materials Discovery and Design.
Cham : Springer, 2018
(OCoLC)1045480220
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Turab Lookman; Stephan Eidenbenz; Frank Alexander; Cris Barnes
ISBN: 9783319994659 3319994654 9783319994666 3319994662
OCLC Number: 1054129034
Description: 1 online resource.
Contents: Dimensions, Bits, and Wows in Accelerating Materials Discovery --
Is Automated Materials Design and Discovery Possible? --
Importance of Feature Selection in Machine Learning and Adaptive Design for Materials --
Bayesian Approaches to Uncertainty Quantification and Structure Refinement from X-Ray Diffraction --
Deep Data Analytics in Structural and Functional Imaging of Nanoscale Materials --
Data Challenges of In Situ X-Ray Tomography for Materials Discovery and Characterization --
Overview of High-Energy X-Ray Diffraction Microscopy (HEDM) for Mesoscale Material Characterization in Three-Dimensions --
Bragg Coherent Diffraction Imaging Techniques at 3rd and 4th Generation Light Sources --
Automatic Tuning and Control for Advanced Light Sources --
Index
Series Title: Springer series in materials science, v. 280.
Responsibility: Turab Lookman, Stephan Eidenbenz, Frank Alexander, Cris Barnes, editors.

Abstract:

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  Read more...

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