REFERENCES

1. Yang, K.; Wang, Y.; Guo, M.; et al. Recent development of advanced precipitation-strengthened Cu alloys with high strength and conductivity: a review. Prog. Mater. Sci. 2023, 138, 101141.

2. He, S. Y.; Xiong, D. B. Application status of copper-based materials in integrated circuits and prospect on their composites with graphene. Chin. J. Nonferrous. Met. 2022, 33, 1349-77. (in Chinese).

3. Shan, L.; Yang, L.; Wang, Y. Improving the high temperature mechanical performance of Cu–Cr alloy induced by residual nano-sized Cr precipitates. Mater. Sci. Eng. A. 2022, 845, 143250.

4. Mishnev, R.; Shakhova, I.; Belyakov, A.; Kaibyshev, R. Deformation microstructures, strengthening mechanisms, and electrical conductivity in a Cu–Cr–Zr alloy. Mater. Sci. Eng. A. 2015, 629, 29-40.

5. Shang, Y.; Xiong, Z.; An, K.; Hauch, J. A.; Brabec, C. J.; Li, N. Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics. MGE. Advances. 2024, 2, e28.

6. Lv, C.; Zhou, X.; Zhong, L.; et al. Machine learning: an advanced platform for materials development and state prediction in lithium-ion batteries. Adv. Mater. 2022, 34, e2101474.

7. Liao, X.; Liao, M.; Wei, C.; et al. A process-structure-property model via physics-based/data-driven hybrid methods for freeze-cast porous ceramics in Si₃N₄-Si₂N₂O case system. Acta. Mater. 2024, 269, 119819.

8. Xi, S.; Yu, J.; Bao, L.; et al. Predicting atomic structure and mechanical properties in quinary L12-Strengthened cobalt-based superalloys using machine learning-driven first-principles calculations. Mater. Today. Commun. 2024, 38, 107774.

9. Chen, Z.; Yang, Y. Data-driven design of eutectic high entropy alloys. J. Mater. Inf. 2023, 3, 10.

10. Jin, H.; Zhang, H.; Li, J.; et al. Discovery of novel two-dimensional photovoltaic materials accelerated by machine learning. J. Phys. Chem. Lett. 2020, 11, 3075-81.

11. Ojih, J.; Onyekpe, U.; Rodriguez, A.; Hu, J.; Peng, C.; Hu, M. Machine learning accelerated discovery of promising thermal energy storage materials with high heat capacity. ACS. Appl. Mater. Interfaces. 2022, 14, 43277-89.

12. Ghorbani, M.; Boley, M.; Nakashima, P.; Birbilis, N. A machine learning approach for accelerated design of magnesium alloys. Part A: Alloy data and property space. J. Magnes. Alloys. 2023, 11, 3620-33.

13. Zhang, X. Q.; Chen, M. Heat treatment schedule model of high strength and high conductivity copper alloy based on RBF artificial neural network. Trans. Mater. Heat. Treat. 2022, 43, 154-60. (in Chinese).

14. Wang, C.; Fu, H.; Jiang, L.; Xue, D.; Xie, J. A property-oriented design strategy for high performance copper alloys via machine learning. npj. Comput. Mater. 2019, 5, 227.

15. Ozerdem, M. S.; Kolukisa, S. Artificial neural network approach to predict the mechanical properties of Cu–Sn–Pb–Zn–Ni cast alloys. Mater. Design. 2009, 30, 764-9.

16. Zhao, Q.; Yang, H.; Liu, J.; Zhou, H.; Wang, H.; Yang, W. Machine learning-assisted discovery of strong and conductive Cu alloys: data mining from discarded experiments and physical features. Mater. Design. 2021, 197, 109248.

17. Villars, P.; Brandenburg, K.; Berndt, M.; et al. Binary, ternary and quaternary compound former/nonformer prediction via Mendeleev number. J. Alloys. Compd. 2001, 317-8, 26-38.

18. Zhang, X.; Zhang, Y.; Tian, B.; et al. Review of nano-phase effects in high strength and conductivity copper alloys. Nanotechnol. Rev. 2019, 8, 383-95.

19. Zhang, H.; Fu, H.; Zhu, S.; Yong, W.; Xie, J. Machine learning assisted composition effective design for precipitation strengthened copper alloys. Acta. Mater. 2021, 215, 117118.

20. Gorsse, S.; Gouné, M.; Lin, W. C.; Girard, L. Dataset of mechanical properties and electrical conductivity of copper-based alloys. Sci. Data. 2023, 10, 504.

21. He, S.; Wang, Y.; Zhang, Z.; et al. Interpretable machine learning workflow for evaluation of the transformation temperatures of TiZrHfNiCoCu high entropy shape memory alloys. Mater. Design. 2023, 225, 111513.

22. Lang, N. D.; Kohn, W. Theory of metal surfaces: work function. Phys. Rev. B. 1971, 3, 1215-23.

23. Lu, H.; Zhao, C.; Wang, H.; Liu, X.; Yu, R.; Song, X. Hardening tungsten carbide by alloying elements with high work function. Acta. Crystallogr. B. Struct. Sci. Cryst. Eng. Mater. 2019, 75, 994-1002.

24. Li, J.; Huang, G.; Mi, X.; Peng, L.; Xie, H.; Kang, Y. Effect of Ni/Si mass ratio and thermomechanical treatment on the microstructure and properties of Cu-Ni-Si alloys. Materials 2019, 12, 2076.

25. Cheng, J.; Tang, B.; Yu, F.; Shen, B. Evaluation of nanoscaled precipitates in a Cu-Ni-Si-Cr alloy during aging. J. Alloys. Compd. 2014, 614, 189-95.

26. Pan, S.; Yu, J.; Han, J.; et al. Customized development of promising Cu-Cr-Ni-Co-Si alloys enabled by integrated machine learning and characterization. Acta. Mater. 2023, 243, 118484.

27. Peng, L. J.; Xie, H. F.; Huang, G. J.; Yang, Z.; Mi, X. J.; Xiong, B. Q. Dynamics of phase transformation in Cu-Cr-Zr alloy. Adv. Mater. Res. 2014, 887-8, 333-7.

28. Sun, Y.; Peng, L.; Huang, G.; Xie, H.; Mi, X.; Liu, X. Effects of Mg addition on the microstructure and softening resistance of Cu–Cr alloys. Mater. Sci. Eng. A. 2020, 776, 139009.

29. Han, Z.; Zhou, M.; Jing, K.; et al. Effect of Mg addition on the microstructure and mechanical properties of Cu-Ti-Zr alloy. J. Alloys. Compd. 2024, 1004, 175897.

30. Ban, Y.; Zhang, Y.; Jia, Y.; et al. Effects of Cr addition on the constitutive equation and precipitated phases of copper alloy during hot deformation. Mater. Design. 2020, 191, 108613.

31. Han, L.; Liu, J.; Tang, H.; Yan, Z. Study of Zr addition on the composition, crystallite size, microstructure and properties of high-performance nano Cu alloys prepared by mechanical alloying. Mater. Chem. Phys. 2022, 290, 126630.

32. Pang, Y.; Xia, C.; Wang, M.; et al. Effects of Zr and (Ni, Si) additions on properties and microstructure of Cu-Cr alloy. J. Alloys. Compd. 2014, 582, 786-92.

33. Li, R.; Kang, H.; Chen, Z.; et al. A promising structure for fabricating high strength and high electrical conductivity copper alloys. Sci. Rep. 2016, 6, 20799.

34. Mirjalili, S.; Mirjalili, S. M.; Lewis, A. Grey wolf optimizer. Adv. Eng. Softw. 2014, 69, 46-61.

35. Tao, S.; Lu, Z.; Jia, L.; Xie, H.; Zhang, J. Effect of Ni/Si mass ratio on microstructure and properties of Cu-Ni-Si alloy. Mater. Res. Express. 2020, 7, 066520.

36. Xue, W.; Xie, G.; Huang, X.; et al. Achieving high strength and high-electrical-conductivity of Cu-Ni-Si alloys via regulating nanoprecipitation behavior through simplified process. J. Mater. Sci. Technol. 2025, 216, 121-9.

37. Su, J.; Dong, Q.; Liu, P.; Li, H.; Kang, B. Research on aging precipitation in a Cu-Cr-Zr-Mg alloy. Mater. Sci. Eng. A. 2005, 392, 422-6.

38. Wang, M.; Yang, Q.; Jiang, Y.; et al. Effects of Fe content on microstructure and properties of Cu-Fe alloy. Trans. Nonferrous. Met. Soc. China. 2021, 31, 3039-49.

39. Wang, W.; Kang, H.; Chen, Z.; et al. Effects of Cr and Zr additions on microstructure and properties of Cu-Ni-Si alloys. Mater. Sci. Eng. A. 2016, 673, 378-90.

40. Zhao, X.; Wang, E.; An, B.; et al. Effects of Sc doping on microstructure and properties of high strength and high conductivity Cu-6 wt%Ag alloy wires with large section size for ultra-high pulsed magnet coils. Mater. Sci. Eng. A. 2025, 927, 148038.

41. Xiao, Z.; Ding, Y.; Wang, Z.; et al. Research and development of advanced copper matrix composites. Trans. Nonferrous. Met. Soc. China. 2024, 34, 3789-821.

42. Zhang, C.; Xiao, X.; Yang, W.; Gao, W.; Li, Q.; He, J. Microstructural evolution and properties of a Cu-Fe-Mn-P alloys with high strength and high conductivity. Mater. Today. Commun. 2024, 39, 108611.

43. Yang, H.; Ma, Z.; Lei, C.; et al. High strength and high conductivity Cu alloys: a review. Sci. China. Technol. Sci. 2020, 63, 2505-17.

44. Zhang, B.; Tao, N.; Lu, K. A high strength and high electrical conductivity bulk Cu-Ag alloy strengthened with nanotwins. Scr. Mater. 2017, 129, 39-43.

45. Kong, L.; Zhu, X.; Xing, Z.; et al. Preparation and mechanisms of Cu-Ag alloy fibers with high strength and high conductivity. Mater. Sci. Eng. A. 2024, 895, 146219.

46. Tian, Y.; Zhang, Z. Bulk eutectic Cu-Ag alloys with abundant twin boundaries. Scr. Mater. 2012, 66, 65-8.

47. Shi, J.; Zhao, L.; Chen, L.; et al. Effect of accelerated Fe-rich precipitation induced by Ag addition on the microstructure and comprehensive properties of Cu–10 Wt Pct Fe alloys. Metall. Mater. Trans. A. 2023, 54, 757-67.