Perspective: Codesign for materials science: An optimal learning approach

A key element of materials discovery and design is to learn from available data and prior knowledge to guide the next experiments or calculations in order to focus in on materials with targeted properties. We suggest that the tight coupling and feedback between experiments, theory and informatics de...

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Bibliographic Details
Published inAPL materials Vol. 4; no. 5; pp. 053501 - 053501-6
Main Authors Lookman, Turab, Alexander, Francis J., Bishop, Alan R.
Format Journal Article
LanguageEnglish
Published United States American Institute of Physics 01.05.2016
AIP Publishing LLC
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Summary:A key element of materials discovery and design is to learn from available data and prior knowledge to guide the next experiments or calculations in order to focus in on materials with targeted properties. We suggest that the tight coupling and feedback between experiments, theory and informatics demands a codesign approach, very reminiscent of computational codesign involving software and hardware in computer science. This requires dealing with a constrained optimization problem in which uncertainties are used to adaptively explore and exploit the predictions of a surrogate model to search the vast high dimensional space where the desired material may be found.
Bibliography:USDOE
ISSN:2166-532X
2166-532X
DOI:10.1063/1.4944627