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Materials genome strategy for metallic glasses

期刊

JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
卷 166, 期 -, 页码 173-199

出版社

JOURNAL MATER SCI TECHNOL
DOI: 10.1016/j.jmst.2023.04.074

关键词

Metallic glasses; Materials genome initiative; High-throughput techniques; Machine learning

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Metallic glasses have unique chemical, physical, and mechanical properties, making them attractive for various engineering applications. Understanding the structure-property relationships is crucial for the development of new metallic glasses with desirable performance. This paper provides an overview of recent advances, challenges, and future opportunities in the field, including high-throughput preparation and characterization of metallic glasses, as well as data-driven machine learning strategies for accelerating their development. The paper also proposes future research directions and perspectives for MGI-assisted design of metallic glasses.
Metallic glasses (MGs) have attracted extensive attention in the past decades due to their unique chem-ical, physical and mechanical properties promising for a wide range of engineering applications. A thor-ough understanding of their structure-property relationships is the key to the development of novel MGs with desirable performance. New strategies, as proposed by Materials Genome Initiative (MGI), construct a new paradigm for high-throughput materials discovery and design, and are being increas-ingly implemented in the search of new MGs. While a few reports have summarized the application of high-throughput and/or machine learning techniques, a comprehensive assessment of materials genome strategies for developing MGs is still missing. Herein, this paper aims to present a timely overview of key advances in this fascinating subject, as well as current challenges and future opportunities. A holistic approach is used to cover the related topics, including high-throughput preparation and characterization of MGs, and data-driven machine learning strategies for accelerating the development of novel MGs. Fi-nally, future research directions and perspectives for MGI-assisted design of MGs are also proposed and surmised. & COPY; 2023 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

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