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Machine learning accelerates the materials discovery
J Fang, M ** the creep life of nickel-based SX superalloys in a large compositional space by a two-model linkage machine learning method
H Han, W Li, S Antonov, L Li - Computational Materials Science, 2022 - Elsevier
Accurate prediction of the creep life is important during the alloy design and optimization of
nickel-based single crystal superalloys, especially for those with expensive alloying …
nickel-based single crystal superalloys, especially for those with expensive alloying …
Recent Advancements in Material Waste Recycling: Conventional, Direct Conversion, and Additive Manufacturing Techniques
To improve the microstructure and mechanical properties of fundamental materials including
aluminum, stainless steel, superalloys, and titanium alloys, traditional manufacturing …
aluminum, stainless steel, superalloys, and titanium alloys, traditional manufacturing …
An explainable machine learning model for superalloys creep life prediction coupling with physical metallurgy models and CALPHAD
Y Huang, J Liu, C Zhu, X Wang, Y Zhou, X Sun… - Computational Materials …, 2023 - Elsevier
Data-driven research mode plays an increasingly important role in scientific research. In this
study, a dimensionality reduction strategy coupling with physical metallurgy models and …
study, a dimensionality reduction strategy coupling with physical metallurgy models and …