Towards optimizing cooling rate, microstructure, and compressive strength in rapidly solidified Cu–20Fe alloy
Source abstract
Abstract
There is currently interest in the development new Cu–Fe alloys with higher Fe content (>5 wt%), a low-cost element. In order to improve electrical, thermal and mechanical properties, there is a need to decrease the size of the Fe-rich phase and improve its distribution, whose possibilities rely on adding alloying third elements and heat treatments. However, the prospect of controlling the size of the phase through dendritic spacing control by means of rapid solidification processes may be feasible and deserves to be explored, as is the case in the present study. The following methods were employed to evaluate the round stepped cast samples of the Cu-20 wt% Fe alloy: centrifugal casting in a Cu mold, optical microscopy, CALPHAD, Scanning Electron Microscopy/Energy Dispersive Spectroscopy (SEM/EDS), X-ray Diffraction (XRD), Vickers hardness, and compressive tests, in samples corresponding to different coarsening microstructures. Finally, dendritic growth is modelled using the Kirkwood equation. The results demonstrate a promising processing route with control of the secondary dendrite arm spacing (SDAS), whose methodology and modeling can serve as a basis for other alternative processes with the Cu–Fe alloys, allowing suitable size and distribution of Fe phase to be attained. It is further demonstrated that the Kirkwood model is able to match experimental SDAS in both slowly and rapidly solidified Cu–Fe samples. While Fe (BCC) is expected to increase strength, this is only slightly observed in the hardness results for smaller SDAS, as the loads are more superficial. In the case of compressive yield strength, SDAS in the observed range (1.4 μm–2.2 μm) is found to have no effect.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Aluminum Alloy Microstructure Properties · Metallurgy and Material Forming · Microstructure and mechanical properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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