Multiscale analysis of grain boundary microstructure in high strength 7xxx Al alloys
Source abstract
Abstract
The size, distribution and chemical composition of grain boundary η-phase precipitates (GBPs) and micro-segregation present in thick plate (140 mm) 7xxx Al alloys has been quantified across a range of length scales. To address the known limitations of individual characterisation methods, a number of cross-correlated, high resolution techniques have been used, including atom probe tomography (APT). A new-generation high-Zn alloy (AA7085) has been compared to a more established material, AA7050, in T7651 temper conditions. The results show that high angle grain boundaries in both alloys are dominated by quench-induced GBPs (Q-GBPs), covering up to ~40% of the area in AA7050. When viewed on brittle intergranular fracture surfaces and in 3D, the Q-GBPs appear much larger than previously reported and exhibit complex branched, dendritic-like morphologies. In AA7050, the Q-GBPs contain substantially higher levels of Cu (by 29 %) and Al (by 37%) and lower Zn (by 33 %) than AA7085. Classical modelling demonstrates that these differences result from different transformation pathways, with precipitates in the more quench sensitive AA7050 alloy nucleating at higher temperatures, which exaggerates the effect of alloy chemistry. In both alloys GB segregation was limited, with low levels of Zn detected relative to the matrix, but more Mg and less Cu in AA7050. It is, therefore, proposed that the higher Cu and Al, and lower Zn content, of the large Q-GBPs present in AA7050 is the main difference in GB microchemistry between the two materials and is the primary reason its GBs are less chemically active. The implications for the relative susceptibilities of the alloys to environmentally assisted cracking are briefly discussed.
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Research context
OpenAlex topics: Aluminum Alloy Microstructure Properties · Microstructure and mechanical properties · Advanced Materials Characterization Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (88)
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