Back to Search
Start Over
The γ/γ′ microstructure in CoNiAlCr-based superalloys using triple-objective optimization
The γ/γ′ microstructure in CoNiAlCr-based superalloys using triple-objective optimization
- Source :
- npj Computational Materials, Vol 9, Iss 1, Pp 1-11 (2023)
- Publication Year :
- 2023
- Publisher :
- Nature Portfolio, 2023.
-
Abstract
- 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%).
Details
- Language :
- English
- ISSN :
- 20573960
- Volume :
- 9
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- npj Computational Materials
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.30cb8eaf152c44ca9cd6af08be17e885
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41524-023-01090-9