摘要
Superalloys are indispensable materials for the fabrication of high-temperature components in aircraft engines.The discovery of a novel class ofγ/γ′Co-Al-W alloys has ignited a surge of interest in Cobased superalloys,with the aspiration to transcend the inherent constraints of their Ni-based counterparts.However,the conventional methodologies utilized in the design and advancement of newγ/γ′Co-based superalloys are frequently characterized by their laborious and resource-intensive nature.In this study,we employed a coupled Density Functional Theory(DFT)and machine learning(ML)approach to predict and analyze the stability of the crucialγ′phase,which is instrumental in expediting the discovery ofγ/γ′Co-based alloys.
基金
supported by National Natural Science Foundation of China(Nos.52371014 and U22B20132)
Shenzhen Science and Technology Program(No.JCYJ20230807091401004)
Fundamental Research Funds for the Central Universities(No.20720230036).
