Accelerated Design of High γ′ Solvus Temperature and Yield Strength Cobalt-Based Superalloy Based on Machine Learning and Phase Diagram
This study combines machine learning and a phase diagram to accelerate the design of a cobalt-based superalloy with a composition of Co-30Ni-10Al-6Ta (at%). The results show that Co-30Ni-10Al-6Ta alloy exhibits high γ′ solvus temperature (1,215 °C) and high yield strength (1,220 Mpa at 25 °C), which...
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Veröffentlicht in: | Frontiers in materials 2022-05, Vol.9 |
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Hauptverfasser: | , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This study combines machine learning and a phase diagram to accelerate the design of a cobalt-based superalloy with a composition of Co-30Ni-10Al-6Ta (at%). The results show that Co-30Ni-10Al-6Ta alloy exhibits high γ′ solvus temperature (1,215 °C) and high yield strength (1,220 Mpa at 25 °C), which is comparable with commercial nickel-based polycrystalline superalloy M-Mar-247. Moreover, the wide processing window and excellent γ′ phase stability make it lucrative for further applications at high temperatures. Meanwhile, the alloy design method also provides a new idea for efficiently realizing the preparation of high-performance alloys. |
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ISSN: | 2296-8016 2296-8016 |
DOI: | 10.3389/fmats.2022.882955 |