Lattice Misfit Predictions via the Gaussian Process Regression for Ni-Based Single Crystal Superalloys

• Published in: Metals and materials international Vol. 27; no. 2; pp. 235 - 253
• Main Authors: Zhang, Yun, Xu, Xiaojie
• Format: Journal Article
• Language: English
• Published: Seoul The Korean Institute of Metals and Materials 01.02.2021; Springer Nature B.V; 대한금속·재료학회
• Subjects: Characterization and Evaluation of Materials; Chemical composition; Chemistry and Materials Science; Cost analysis; Creep strength; Crystal lattices; Deformation mechanisms; Engineering Thermodynamics; Gaussian process; Heat and Mass Transfer; High temperature; Machines; Magnetic Materials; Magnetism; Manufacturing; Materials Science; Mechanical properties; Metallic Materials; Nickel; Nickel base alloys; Processes; Regression analysis; Regression models; Single crystals; Solid Mechanics; Superalloys; 재료공학; Ni-based single crystal superalloys; Lattice constant; Lattice mismatch; Machine learning

Ni-based single crystal superalloys exhibit superb mechanical strength, particularly, creep resistance at elevated temperature. The unique microstructure, which is consisted of γ and γ ′ phases, is a major factor that determines the mechanical behavior of these alloys. The lattice misfit between the...