Integrating Machine Learning and Thermodynamic Descriptors for Enhanced Ni-Based Single Crystal Superalloys Creep Life Prediction and Alloy Design

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International Pub Date : 2025-03-22 DOI:10.1007/s12540-025-01906-x

Jian Yao, Wanchan Yu, Juncheng Wang, Longfei Zhang, Feng Liu, Weifu Li, Liming Tan, Lan Huang, Yong Liu

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Abstract

Ni-based single crystal superalloys play a vital role in critical areas such as aerospace and gas turbines due to their superior high-temperature strength. However, accurately predicting the creep rupture life of these alloys has been a challenge. In this study, an artificial neural network-based prediction model was developed to effectively improve the accuracy of creep life prediction for Ni-based single crystal superalloys by incorporating 15 new descriptors. The R² for the test set was 0.8595. Further, the SHAP value results guided the design of new low-cost, high-performance alloys, among which the new designed alloy (5.91 Cr, 6.21 Co, 1.62 Mo, 6.37 W, 5.64 Al, 7.22 Ta, 1.45 Re, 0.52 Ti and Ni balance, wt%) showed a higher creep life than the existing alloy CMSX-4, while having a Re content < 1.5 wt%. The results not only provide new tools for superalloy design, but also confirm the practical value of machine learning in materials science.

Graphical Abstract

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集成机器学习和热力学描述符增强镍基单晶高温合金蠕变寿命预测和合金设计

镍基单晶高温合金由于其优越的高温强度，在航空航天和燃气轮机等关键领域发挥着至关重要的作用。然而，准确预测这些合金的蠕变断裂寿命一直是一个挑战。为了有效提高镍基单晶高温合金蠕变寿命预测的精度，本研究建立了一种基于人工神经网络的预测模型，引入了15个新的描述符。检验集的R2为0.8595。此外，SHAP值结果指导了新型低成本高性能合金的设计，其中新设计的合金（5.91 Cr, 6.21 Co, 1.62 Mo, 6.37 W, 5.64 Al, 7.22 Ta, 1.45 Re， 0.52 Ti和Ni平衡，wt%）比现有合金CMSX-4具有更高的蠕变寿命，而Re含量为<； 1.5 wt%。这一结果不仅为高温合金设计提供了新的工具，也证实了机器学习在材料科学中的实用价值。图形抽象

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来源期刊

Metals and Materials International 工程技术-材料科学：综合

CiteScore

7.10

自引率

8.60%

发文量

197

审稿时长

3.7 months

期刊介绍： Metals and Materials International publishes original papers and occasional critical reviews on all aspects of research and technology in materials engineering: physical metallurgy, materials science, and processing of metals and other materials. Emphasis is placed on those aspects of the science of materials that are concerned with the relationships among the processing, structure and properties (mechanical, chemical, electrical, electrochemical, magnetic and optical) of materials. Aspects of processing include the melting, casting, and fabrication with the thermodynamics, kinetics and modeling.