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Merging Materials and Data Science: Opportunities, Challenges, and Education in Materials Informatics

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Abstract

Since the launch of the Materials Genome Initiative (MGI) the field of materials informatics (MI) emerged to remove the bottlenecks limiting the pathway towards rapid materials discovery. Although the machine learning (ML) and optimization techniques underlying MI were developed well over a decade ago, programs such as the MGI encouraged researchers to make the technical advancements that make these tools suitable for the unique challenges in materials science and engineering. Overall, MI has seen a remarkable rate in adoption over the past decade. However, for the continued growth of MI, the educational challenges associated with applying data science techniques to analyse materials science and engineering problems must be addressed. In this paper, we will discuss the growing use of materials informatics in academia and industry, highlight the need for educational advances in materials informatics, and discuss the implementation of a materials informatics course into the curriculum to jump-start interested students with the skills required to succeed in materials informatics projects.

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Authors and Affiliations

  1. Department of Materials Science and Engineering, North Carolina State University, 911 Partners Way, Raleigh, NC, 27695-7907, USA

    Thomas J. Oweida, Akhlak Mahmood, Matthew D. Manning, Sergei Rigin & Yaroslava G. Yingling

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  1. Thomas J. Oweida
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  2. Akhlak Mahmood
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  3. Matthew D. Manning
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  5. Yaroslava G. Yingling
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Oweida, T.J., Mahmood, A., Manning, M.D. et al. Merging Materials and Data Science: Opportunities, Challenges, and Education in Materials Informatics. MRS Advances 5, 329–346 (2020). https://doi.org/10.1557/adv.2020.171

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