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
Hauptverfasser: Wang, Cuiping, Chen, Xin, Chen, Yuechao, Yu, Jinxin, Cai, Wensu, Chen, Zhongfeng, Yu, Xiang, Li, Yingju, Yang, Yuansheng, Liu, Xingjun
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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.
ISSN:2296-8016
2296-8016
DOI:10.3389/fmats.2022.882955