fig12

Machine learning-driven new paradigm for Co-based superalloys

Figure 12. Alloy design workflow. Composition-dependent maps of (A) γ′ solvus temperature and (B) γ′ area fraction for Co-V-Ta ternary alloys after 800 °C/600 h annealing predicted by ML; SEM images of (C) Co-6V-2.5Ta and (D) Co-10V-2.5Ta alloys after 800 °C/360 h annealing; Thermo-Calc-calculated grain boundary segregation in (E) Co-6V-2.5Ta, (F) Co-10V-2.5Ta, and (G) Co-12V-2Ta alloys; (H) Ta content comparison across (E)-(G); SEM images of Co-12V-2Ta alloy after (I) 720 h and (J) 48 h annealing at 800 °C[77]. ML: Machine learning; SEM: scanning electron microscopy.

Journal of Materials Informatics
ISSN 2770-372X (Online)
Follow Us

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/