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Data-Augmented Structure-Property Mapping for Accelerating Computational Design of Advanced Material Systems

Abstract Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the lear... (more)
Created Date 2018
Contributor Cang, Ruijin (Author) / Ren, Yi (Advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Subject Mechanical engineering / Materials Science / Deep Learning / Integrated Computational Material Engineering / Material Microstructure / Meta Learning / Structure-Property Mapping
Type Doctoral Dissertation
Extent 164 pages
Language English
Note Doctoral Dissertation Mechanical Engineering 2018
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis