The effect of metalloid content on glass forming ability, thermal stability and magnetic properties of Fe-Ta-Si-C powders prepared by mechanical alloying
Source abstract
Abstract
Abstract In this study, the structural, thermal and magnetic characteristics of Fe75-xTa5Si10C10+x (x = 0, 5, 10) powders processed by mechanical alloying (MA) were investigated. The X-ray diffraction (XRD) indicated that by increasing the level of carbon, the structural refinement and lattice strain of the nanocrystalline Fe-based solid solution formed in the early stages of milling are enhanced. Furthermore, quantitative XRD analyses demonstrated that the glass forming ability (GFA) is remarkably improved by increasing the amount of carbon, where the percentage of amorphous phase increases from 56% for x = 0 to 98% for x = 10 after 120 h of milling. In addition, thermodynamic calculations, based on the extended Miedema's model, showed that the driving force for the glass formation increases with the concentration of carbon. Also, thermal analyses demonstrated that both the glass transition (Tg) and the onset of the crystallization (Tx) temperatures increase with the content of carbon, suggesting an enhanced thermal stability of the glassy phase. Additionally, the extension of the supercooled liquid region for the alloys with x = 5 and 10 reached a large value of 75 and 78 K, respectively, manifesting a high thermal stability of their supercooled liquid. Magnetic measurements showed that the soft magnetic behavior of the powders milled for 120 h is improved by increasing the level of carbon in terms of a decrease in coercivity (Hc) from 3.7 kA/m for x = 0 to 2.1 kA/m for x = 10. The evolution of the magnetic properties with annealing temperature reflected that the alloy with x = 10 displays a minimum Hc of 1.2 kA/m after annealing at 673 K.
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Research context
OpenAlex topics: Metallic Glasses and Amorphous Alloys · Microstructure and Mechanical Properties of Steels · Metal Alloys Wear and Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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