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説明:

This review systematically analyzes over 200 publications to explore the growing role of data-driven methods and their potential benefits in accelerating alloy development. The review presents a comprehensive overview of different aspects of alloy innovation by machine learning and other computational approaches used in recent years.
These methods harness the power of advanced simulation techniques and data analytics to expedite materials’ discovery, predict properties, and optimize performance.
Through analysis, significant trends and disparities within the data discerned, while highlighting previously overlooked research gaps, thus underscoring areas that require further exploration.

権利情報:

• Creative Commons BY-NC Attribution-NonCommercial 4.0 International
  

キーワード: Alloy development, machine learning, data-driven research, materials informatics, Materials Genome Initiative, Materials databases

刊行年月日: 2024-12-31

出版者: Informa UK Limited

掲載誌:

• Science and Technology of Advanced Materials: Methods (ISSN: 27660400) vol. 4 issue. 1 2326305

研究助成金:

• D3090

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1080/27660400.2024.2326305

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更新時刻: 2024-06-25 12:30:16 +0900

MDRでの公開時刻: 2024-06-25 12:30:16 +0900