Gaps and Barriers to Successful Integration and Adoption of Practical Materials Informatics Tools and Workflows
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https://doi.org/10.1007/s11837-020-04434-8 Ó 2020 The Minerals, Metals & Materials Society
AUGMENTING PHYSICS-BASED MODELS IN ICME WITH MACHINE LEARNING AND UNCERTAINTY QUANTIFICATION
Gaps and Barriers to Successful Integration and Adoption of Practical Materials Informatics Tools and Workflows DAVID L. MCDOWELL1,2,3 1.—Woodruff School of Mechanical Engineering, Atlanta, USA. 2.—School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA. 3.—e-mail: [email protected]
Preparation of the future materials workforce consistent with major imperatives rooted in integrated computational materials engineering (ICME) and the materials genome initiative (MGI) is most effectively pursued within the vision of a materials innovation ecosystem that spans across conventional engineering, science, and computing disciplines. The ICME foundation integrates principles of materials science with computational methods, including increasing reliance on modern data science methods that are savvy to digital information that recognizes hierarchical material structure and the need for correlative relations for process-structure and structure-property relations. We consider gaps in academic research and education programs related to systems engineering, uncertainty quantification of both experiments and computation, and data science methods. Barriers to the introduction of materials data science are discussed, as well as opportunities for innovation in educating the future MGI and ICME workforce.
INTRODUCTION Materials science and engineering (MSE) was established as an academic discipline in the latter half of the twentieth century. Particularly in the last 10 years, new initiatives have taken hold that have been embraced by industry and the research community and require the leveraging of advances in computing and modern data science: integrated computational materials engineering (ICME) and the Materials Genome Initiative (MGI). These initiatives serve as harbingers of future workforce needs in materials discovery, development, and product deployment. As in all branches of economics, business, science, and engineering, modern materials science is compelled to effectively integrate modern data science with the digital information which is so prevalent in this field to enhance productivity and increase the rate of progress in R&D. Broadly speaking, the materials (Received July 14, 2020; accepted October 5, 2020)
industry, government, and academic cohorts are still in the early stages of responding to this imperative. The ICME initiative emerged from a 2008 National Academy of Engineering National Materials Advisory Board report.1 ICME addresses the historical difficulty in bridging the gap that exists between new and improved material concepts developed in basic research and their deployment into products, the so-called valley of death. ICME represents an approach to the design and development of materials that considers product requirements and chiefly focuses on integration of modeli
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