REFERENCES

1. Sato J, Omori T, Oikawa K, Ohnuma I, Kainuma R, Ishida K. Cobalt-base high-temperature alloys. Science 2006;312:90-1.

2. Zhuang X, Antonov S, Li L, Feng Q. γ’-strengthened multicomponent CoNi-based wrought superalloys with improved comprehensive properties. Metall Mater Trans A 2023;54:1671-82.

3. Bauer A, Neumeier S, Pyczak F, Göken M. Microstructure and creep strength of different γ/γ’-strengthened Co-base superalloy variants. Scripta Materialia 2010;63:1197-200.

4. Neumeier S, Freund LP, Bezold A, et al. Advanced polycrystalline γ’-strengthened CoNiCr-based superalloys. Metall Mater Trans A 2024;55:1319-37.

5. Li J, Zhang J, Li Z, et al. Effect of Ti/Nb/Ta addition on the γ/γ’ coherent microstructure in low-density and high-strength Co-Al-W-Mo-based superalloys. J Mater Sci Technol 2024;186:174-87.

6. Wang C, Zhuo H, Zheng D, et al. Development of a low-density Co-Ni-Al-Ta-Cr superalloy with high mechanical performance and superior oxidation resistance. Mater Des 2024;238:112673.

7. Sun L, Cao B, Ma Q, et al. Machine learning-assisted composition design of W-free Co-based superalloys with high γ’-solvus temperature and low density. J Mater Res Technol 2024;29:656-67.

8. Yang Z, Liu X, Zhao J, et al. Discontinuous coarsening leads to unchanged tensile properties in high-entropy alloys with different recrystallization volume fractions. Int J Plast 2024;176:103963.

9. Lin M, Lu J, Chen Y, et al. 800°C-stable D0₂₂ superlattice in a NiCrFe-based medium entropy alloy. Mater Res Lett 2024;12:172-9.

10. He F, Chen D, Han B, et al. Design of D0₂₂ superlattice with superior strengthening effect in high entropy alloys. Acta Mater 2019;167:275-86.

11. Li X, Ma Q, Liu E, et al. Order phase transition of HIP nickel-based powder superalloy during isothermal aging. J Alloys Compd 2025;1010:177269.

12. He F, Zhang K, Yeli G, et al. Anomalous effect of lattice misfit on the coarsening behavior of multicomponent L1₂ phase. Scr Mater 2020;183:111-6.

13. Mukhopadhyay S, Pandey P, Baler N, Biswas K, Makineni SK, Chattopadhyay K. The role of Ti addition on the evolution and stability of γ/γ’ microstructure in a Co-30Ni-10Al-5Mo-2Ta alloy. Acta Mater 2021;208:116736.

14. Liu P, Huang H, Wen C, Lookman T, Su Y. The γ/γ’ microstructure in CoNiAlCr-based superalloys using triple-objective optimization. npj Comput Mater 2023;9:1090.

15. Liu P, Huang H, Jiang X, et al. Evolution analysis of γ’ precipitate coarsening in Co-based superalloys using kinetic theory and machine learning. Acta Mater 2022;235:118101.

16. Zhuang X, Antonov S, Li W, Lu S, Li L, Feng Q. Alloying effects and effective alloy design of high-Cr CoNi-based superalloys via a high-throughput experiments and machine learning framework. Acta Mater 2023;243:118525.

17. Boddupalli N, Matchen T, Moehlis J. Symbolic regression via neural networks. Chaos 2023;33:083150.

18. Lundberg S, Lee SI. A unified approach to interpreting model predictions. arXiv 2017;arXiv:1705.07874. Available from: https://arxiv.org/abs/1705.07874. [Last accessed on 21 Dec 2024]

19. Garreau D, Luxburg U. Explaining the explainer: a first theoretical analysis of LIME. arXiv 2020;arXiv:2001.03447. Available from: https://arxiv.org/abs/2001.03447. [Last accessed on 21 Dec 2024]

20. Xiong J, Bai B, Jiang H, Faus-golfe A. Determinants of saturation magnetic flux density in Fe-based metallic glasses: insights from machine-learning models. Rare Met 2024;43:5256-67.

21. Xiong J, Lei T, Fu D, Wu J, Zhang T. Data driven discovery of an analytic formula for the life prediction of Lithium-ion batteries. Prog Nat Sci Mater Int 2022;32:793-9.

22. Xiong J, Zhang T, Shi S. Machine learning of mechanical properties of steels. Sci China Technol Sci 2020;63:1247-55.

23. Xiong J, Shi S, Zhang T. A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys. Mater Des 2020;187:108378.

24. Meher S, Nag S, Tiley J, Goel A, Banerjee R. Coarsening kinetics of γ’ precipitates in cobalt-base alloys. Acta Mater 2013;61:4266-76.

25. Zhou H, Xue F, Chang H, Feng Q. Effect of Mo on microstructural characteristics and coarsening kinetics of γ’ precipitates in Co–Al–W–Ta–Ti alloys. J Mater Sci Technol 2018;34:799-805.

26. Chen Y, Wang C, Ruan J, et al. Development of low-density γ/γ’ Co–Al–Ta-based superalloys with high solvus temperature. Acta Mater 2020;188:652-64.

27. Chen Y, Wang C, Ruan J, et al. High-strength Co–Al–V-base superalloys strengthened by γ’-Co₃(Al,V) with high solvus temperature. Acta Mater 2019;170:62-74.

28. Vorontsov V, Barnard J, Rahman K, Yan H, Midgley P, Dye D. Coarsening behaviour and interfacial structure of γ’ precipitates in Co-Al-W based superalloys. Acta Mater 2016;120:14-23.

29. Zhuang X, Antonov S, Li L, Feng Q. Effect of alloying elements on the coarsening rate of γ’ precipitates in multi-component CoNi-based superalloys with high Cr content. Scr Mater 2021;202:114004.

30. Lifshitz I, Slyozov V. The kinetics of precipitation from supersaturated solid solutions. J Phys Chem Solids 1961;19:35-50.

31. Ardell AJ, Ozolins V. Trans-interface diffusion-controlled coarsening. Nat Mater 2005;4:309-16.

32. Zhang J, Liu L, Huang T, et al. Coarsening kinetics of γ’ precipitates in a Re-containing Ni-based single crystal superalloy during long-term aging. J Mater Sci Technol 2021;62:1-10.

33. Gusak A, Lutsenko G, Tu K. Ostwald ripening with non-equilibrium vacancies. Acta Mater 2006;54:785-91.

34. Sun W. Kinetics for coarsening co-controlled by diffusion and a reversible interface reaction. Acta Mater 2007;55:313-20.

35. Calderon H, Voorhees P, Murray J, Kostorz G. Ostwald ripening in concentrated alloys. Acta Metall Mater 1994;42:991-1000.

36. Khatavkar N, Singh AK. Combined approach to capture the evolution of oxidation of Nickel based superalloys using data driven approaches. Phys Rev Mater 2024;8:053601.

37. Wu J, Li Y, Qiao H, Yang Y, Zhao J, Huang Z. Prediction of mechanical properties and surface roughness of FGH4095 superalloy treated by laser shock peening based on XGBoost. J Alloys Metall Syst 2023;1:100001.

38. Ma C, Tang Y, Bao G. Machine learning-based prediction and generation model for creep rupture time of Nickel-based alloys. Comput Mater Sci 2024;233:112736.

39. Mythreyi OV, Srinivaas MR, Amit Kumar T, Jayaganthan R. Machine-learning-based prediction of corrosion behavior in additively manufactured inconel 718. Data 2021;6:80.

40. Chen TQ, Guestrin C. XGBoost: a scalable tree boosting system. arXiv 2016;arXiv:1603.02754. Available from: https://arxiv.org/abs/1603.02754. [Last accessed on 21 Dec 2024]

41. Belkina AC, Ciccolella CO, Anno R, Halpert R, Spidlen J, Snyder-Cappione JE. Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets. Nat Commun 2019;10:5415.

42. Gan W, Gao H, Wen Z. Based on damage caused by microstructure evolution during long-term thermal exposure to analyze and predict creep behavior of Ni-based single crystal superalloy. AIP Advances 2020;10:085301.

43. Qu S, Li Y, Wang C, et al. Coarsening behavior of γ’ precipitates and compression deformation mechanism of a novel Co–V–Ta–Ti superalloy. Mater Sci Eng A 2020;787:139455.

44. Reed RC. The superalloys: fundamentals and applications. Available from: https://www.researchgate.net/publication/287242590_The_Superalloys_Fundamentals_and_Applications. [Last accessed on 21 Dec 2024].

45. Zhang X, Shang H, Gao Q, et al. Coarsening evolution of γ’ phase and failure mechanism of Co-Ni-Al-Ti-based superalloys during isothermal aging. Front Mater 2022;9:863305.

46. Shang H, Ma Q, Gao Q, et al. Yield strength anomaly evaluation of W-free Co-Ni-Al-based superalloys during high temperature tensile tests. Mater Charact 2022;192:112242.

47. Gao Q, Shang H, Ma Q, et al. Isothermal oxidation behavior of W-free Co–Ni–Al-based superalloy at high temperature. Mater Charact 2022;73:513-25.

48. Gao Q, Jiang Y, Liu Z, et al. Effects of alloying elements on microstructure and mechanical properties of Co–Ni–Al–Ti superalloy. Mater Sci Eng A 2020;779:139139.