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The γ/γ′ microstructure in CoNiAlCr-based superalloys using triple-objective optimization

التفاصيل البيبلوغرافية
العنوان: The γ/γ′ microstructure in CoNiAlCr-based superalloys using triple-objective optimization
المؤلفون: Pei Liu, Haiyou Huang, Cheng Wen, Turab Lookman, Yanjing Su
المصدر: npj Computational Materials, Vol 9, Iss 1, Pp 1-11 (2023)
بيانات النشر: Nature Portfolio, 2023.
سنة النشر: 2023
المجموعة: LCC:Materials of engineering and construction. Mechanics of materials
LCC:Computer software
مصطلحات موضوعية: Materials of engineering and construction. Mechanics of materials, TA401-492, Computer software, QA76.75-76.765
الوصف: Abstract Optimizing several properties simultaneously based on small data-driven machine learning in complex black-box scenarios can present difficulties and challenges. Here we employ a triple-objective optimization algorithm deduced from probability density functions of multivariate Gaussian distributions to optimize the γ′ volume fraction, size, and morphology in CoNiAlCr-based superalloys. The effectiveness of the algorithm is demonstrated by synthesizing alloys with desired γ/γ′ microstructure and optimizing γ′ microstructural parameters. In addition, the method leads to incorporating refractory elements to improve γ/γ′ microstructure in superalloys. After four iterations of experiments guided by the algorithm, we synthesize sixteen alloys of relatively high creep strength from ~120,000 candidates of which three possess high γ′ volume fraction (>54%), small γ′ size (77%).
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2057-3960
Relation: https://doaj.org/toc/2057-3960
DOI: 10.1038/s41524-023-01090-9
URL الوصول: https://doaj.org/article/30cb8eaf152c44ca9cd6af08be17e885
رقم الأكسشن: edsdoj.30cb8eaf152c44ca9cd6af08be17e885
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20573960
DOI:10.1038/s41524-023-01090-9