Segregation-induced abnormal recrystallization behavior, texture evolution, and effects on mechanical properties in twin-roll casting 2060 Al-Cu-Li alloys
Source abstract
Abstract
Twin-roll casting (TRC) faces persistent segregation challenges limiting widespread use., Leveraging a comprehensive suite of techniques—electron probe microanalyzer (EPMA), electron back-scattered diffraction (EBSD), and transmission electron microscope (TEM)—and rooted in a thermo-mechanical-solute integrative simulation, this study focus on a detailed exposition of the structural evolution of the 2060 Al-Cu-Li alloy, encompassing its segregation tendencies and textural transformations throughout its processing trajectory. High and low-stress TRC scenarios, TRC-3 and TRC-6, are explored. Empirical observations ascertained that the TRC venture, particularly in TRC-3, cultivates a pronounced segregation gradient, a direct offshoot of the stress gradient, thereby inducing textural disparities. During the homogenization phase, the TRC structure with diminished segregation (TRC-6) manifested signs of recovery and sustained recrystallization, an environment amiable to compositional homogeneity and tempering the pre-existing segregation. In the terminal state, a pioneering discovery elucidated that heightened segregation precipitated the β-fiber textural enhancement mechanism—a phenomenon that deteriorates properties due to the discrepancy in segregation-induced hardness. With astutely managed segregation, TRC-6 recorded tensile strengths and elongation values of 563 MPa and 7.1 % respectively, marking an increment by 20.0 % and 208.7 % in comparison to TRC-3. This research offers vital insights into solute gradients, providing a new perspective on gradient materials.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Aluminum Alloy Microstructure Properties · Microstructure and mechanical properties · Aluminum Alloys Composites Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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