TY - JOUR
T1 - Multiscale modeling of materials
T2 - Computing, data science, uncertainty and goal-oriented optimization
AU - Kovachki, Nikola
AU - Liu, Burigede
AU - Sun, Xingsheng
AU - Zhou, Hao
AU - Bhattacharya, Kaushik
AU - Ortiz, Michael
AU - Stuart, Andrew
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/2
Y1 - 2022/2
N2 - The recent decades have seen various attempts at accelerating the process of developing materials targeted towards specific applications. The performance required for a particular application leads to the choice of a particular material system whose properties are optimized by manipulating its underlying microstructure through processing. The specific configuration of the structure is then designed by characterizing the material in detail, and using this characterization along with physical principles in system level simulations and optimization. These have been advanced by multiscale modeling of materials, high-throughput experimentations, materials data-bases, topology optimization and other ideas. Still, developing materials for extreme applications involving large deformation, high strain rates and high temperatures remains a challenge. This article reviews a number of recent methods that advance the goal of designing materials targeted by specific applications.
AB - The recent decades have seen various attempts at accelerating the process of developing materials targeted towards specific applications. The performance required for a particular application leads to the choice of a particular material system whose properties are optimized by manipulating its underlying microstructure through processing. The specific configuration of the structure is then designed by characterizing the material in detail, and using this characterization along with physical principles in system level simulations and optimization. These have been advanced by multiscale modeling of materials, high-throughput experimentations, materials data-bases, topology optimization and other ideas. Still, developing materials for extreme applications involving large deformation, high strain rates and high temperatures remains a challenge. This article reviews a number of recent methods that advance the goal of designing materials targeted by specific applications.
KW - Machine learning
KW - Materials by design
KW - Multiscale modeling
KW - Uncertainty quantification
UR - http://www.scopus.com/inward/record.url?scp=85120746490&partnerID=8YFLogxK
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U2 - 10.1016/j.mechmat.2021.104156
DO - 10.1016/j.mechmat.2021.104156
M3 - Article
AN - SCOPUS:85120746490
SN - 0167-6636
VL - 165
JO - Mechanics of Materials
JF - Mechanics of Materials
M1 - 104156
ER -