Grain and texture evolution in nano/ultrafine-grained bimetallic Al/Ni composite during accumulative roll bonding
Source abstract
Abstract
The evolution of grain structure during plastic deformation has a significant effect on texture variations and, in turn, the material properties. However, the metal physics leading to a stationary grain size regime in rolled Al combined with a harder phase remains poorly understood. Therefore, the grain and texture evolution in the Al phase and the possible grain coarsening mechanisms operating during accumulative roll bonding (ARB) were investigated in this work. Three ARB cycles were performed at room temperature with the aim of obtaining a bimetallic Al–Ni composite. The microstructure and texture evolutions in this composite were characterized via field emission gun scanning electron microscopy combined with electron backscatter diffraction. With increasing strain, the lamellar grain structure of Al developed into a semi-equiaxed grain structure. Correspondingly, the grain length and thickness decreased from 672 to 0.84 µm and 24.8 to 0.60 µm, respectively. Grain fragmentation was, however, most efficient in the initial stages of rolling, since continuous dynamic recrystallization prevented further grain refinement especially in the last cycle. Consequently, after a strain of 2.7, the refinement continued at decreasing rates, yielding a fragmentation ratio of one at a lower strain than that reported for single-phase Al composites. The mid-section layers of the Al phase were characterized by a mixture of shear and plane strain compression textures. After the third ARB cycle, the Al phase was characterized by a near random texture resulting from grain fragmentation. This fragmentation was induced by local plastic flow in the Al phase, owing to the presence of hard Ni fragments.
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Research context
OpenAlex topics: Microstructure and mechanical properties · Aluminum Alloys Composites Properties · Metallurgy and Material Forming
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (58)
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