The Influence of High Temperature Ultrasonic Processing Time on the Microstructure and Mechanical Properties AZ91E Magnesium Alloy
Source abstract
Abstract
The reduction of harmful greenhouse gas emissions can be realized by utilizing lightweight structural metals, such as magnesium (Mg). Magnesium alloys have the potential to replace higher-density aluminum and ferrous components in automotive and aerospace industries, thereby decreasing vehicle weight and the associated fuel requirements. However, their strength and ductility must be improved to ensure widespread application. This goal can be achieved through ultrasonic processing, a technique that is gaining popularity in the manufacturing of light alloys. In this study, the effects of high-intensity ultrasonic vibration on the microstructure and mechanical properties of AZ91E were investigated. The molten alloys were subjected to 60, 120, 180 and 240 s of sonication at a frequency and amplitude of 20 kHz and 30 µm, respectively. The resultant castings were characterized using optical microscopy, scanning electron microscopy and tensile testing. Sonication was found to improve the mechanical properties of the alloy relative to the base condition. The improvement was attributed to the refinement of the Mg grain structure, decreased area fraction and average size of the brittle Mg17Al12 eutectic phase, in addition to increased area fraction, homogenous distribution and spheroidization of the Mn-Al intermetallic phase. The refinement in microstructure was determined to be a result of improved nucleation and cavitation-induced undercooling of the melt as well as a finer grain size. Therefore, ultrasonic processing can enhance the viability of Mg alloys as engineering materials, offering important opportunities for the production of greener, light-metal components.
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Research context
OpenAlex topics: Magnesium Alloys: Properties and Applications · Aluminum Alloys Composites Properties · Aluminum Alloy Microstructure Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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