Synchronously enhancing the strength, toughness, and stress corrosion resistance of high-end aluminum alloys via interpretable machine learning

Strength, toughness, and stress corrosion resistance are critical properties of aluminum alloys for high-end equipment manufacturing. Unfortunately, the situation of complex alloy composition, diverse aging systems, and conflicting property relationships hinder the synchronous enhancement of three properties. Here, we proposed an interpretable machine learning design strategy for high-end aluminum alloy. The critical intrinsic factors and explicit laws of elements affecting the ultimate tensile strength (UTS), fracture toughness (KIC), and stress corrosion sensitivity factor (ISSRT) of alloys were excavated: The elements with large number of electrons in d-valence electron orbitals, high boiling point, and low nuclear electron distance help enhance the UTS; The elements with low density and minimized difference in first ionization energy with aluminum help improve the KIC; The elements with high diffusion activation energy in aluminum and high corrosion potential in seawater help reduce the ISSRT. Based on the above findings, three microalloying elements of Ti, Cr, and Zr, which have the remarkable combined effect of enhancing synchronously the three properties, were selected, and a new advanced aluminum alloy Al-10.50Zn-2.31Mg-1.56Cu-0.09Ti-0.15Cr-0.10Zr was designed. The UTS, KIC, and ISSRT were 760±4MPa, 34.9±0.3MPa·m1/2, and 13.3%±1.7%, respectively, after RRA treatment. Microstructure analysis revealed that the new alloy had almost no micron secondary phase after RRA treatment, reducing the sites for pitting and cavity formation. The addition of Ti, Cr, and Zr formed dispersoids Al18(Cr,Ti)2Mg3 and Al3Zr, which contributed to the synchronous improvement of strength, toughness, and stress corrosion resistance. The high-volume fraction of precipitates significantly enhanced the strength of the alloy.