Prospective paper: Machine learning for composite materials

January 22, 2020


Abstract: Machine learning (ML) has been perceived as a promising tool for the design and discovery of novel materials for a broad range of applications. In this prospective paper, we summarize recent progress in the applications of ML to composite materials modeling and design. An overview of how different types of ML algorithms can be applied to accelerate composite research is presented. This framework is envisioned to revolutionize approaches to design and optimize composites for the next generation of materials with unprecedented properties.


Full paper: CT Chen and GX Gu, Machine learning for composite materials, MRS Communications, 2019, DOI: 10.1557/mrc.2019.32

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© 2017 by Chun-Teh Chen

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