The retrogression and re-aging (RRA) processes, aimed mainly at tailoring intergranular precipitates, could significantly improve the corrosion resistance (i.e., stress corrosion cracking resistance) without considerably decreasing the strength, which signifies that an efficient control of the size, distribution and evolution of intergranular and intragranular precipitates becomes critical for the integrated properties of the (mid-)thick high-strength Al alloy plates. Compared to RRA process with retrogression at 200 °C (T77), this study investigated the impact of a modified RRA process (MT77) with lower retrogression temperatures (155-175 °C) and first-stage under-aging on the properties of a high-strength AA7050 Al alloy, in combination with detailed precipitate characterization. The study showed that the strength/microhardness of the RRA-treated alloys decreased with raising retrogression temperature and/or prolonging retrogression time, along with the increased electrical conductivity. The rapid responsiveness of microstructure/property typical of retrogression at 200 °C was obviously postponed or decreased by using MT77 process with longer retrogression time that was more suitable for treating the (mid-)thick plates. On the other hand, higher retrogression temperature facilitated more intragranular η precipitates, coarse intergranular precipitates and wide precipitate free zones, which prominently increased the electrical conductivity alongside a considerable strength loss as compared to the MT77-treated alloys. With the preferred MT77 process, the high strength approaching T6 level as well as good corrosion resistance was achieved. However, though a relatively homogeneous through-thickness strength was obtained, some small discrepancies of properties between the central and surface areas of an 86-mm thick 7050 Al alloy plate were observed, possibly related to the quenching sensitivity. The precipitate evolution and mechanistic connection to the properties were discussed and reviewed for high-strength Al alloys along with suggestions for further RRA optimization.
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