Machine learning materials physics: Surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics

Title
Machine learning materials physics: Surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics
Authors
Keywords
Deep Neural Networks, Mechanochemistry, Phase field, Heterogeneous computing
Journal
Publisher
Elsevier BV
Online
2018-10-29
DOI
10.1016/j.cma.2018.10.025

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