No abstract

In this work, the design, microstructures and mechanical properties of five novel non-equiatomic lightweight medium entropy alloys were studied. The manufactured alloys were based on the Al 65 Cu 5 Mg 5 Si 15 Zn 5 X 5 and Al 70 Cu 5 Mg 5 Si 10 Zn 5 X 5 systems. The formation and presence of phases and microstructures were studied by introducing Fe, Ni, Cr, Mn and Zr. The feasibility of CALPHAD method for the design of new alloys was studied, demonstrating to be a good approach in the design of medium entropy alloys, due to accurate prediction of the phases, which were validated via X-ray diffraction and scanning electron microscopy with energy dispersive spectroscopy. In addition, the alloys were manufactured using an industrial-scale die-casting process to make the alloys viable as engineering materials. In terms of mechanical properties, the alloys exhibited moderate plastic deformation and very high compressive strength up to 644 MPa. Finally, the reported microhardness value was in the range of 200 HV 0.1 to 264 HV 0.1 , which was two to three times higher than those of commercial Al alloys.

In this work, three novel complex concentrated aluminum alloys were developed. To investigate the unexplored region of the multicomponent phase diagrams, thermo-physical parameters and the CALPHAD method were used to understand the phase formation of the Al80Mg5Sn5Zn5Ni5, Al80Mg5Sn5Zn5Mn5, and Al80Mg5Sn5Zn5Ti5 alloys. The ingots of the alloys were manufactured by a gravity permanent mold casting process, avoiding the use of expensive, dangerous, or scarce alloying elements. The microstructural evolution as a function of the variable element (Ni, Mn, or Ti) was studied by means of different microstructural characterization techniques. The hardness and compressive strength of the as-cast alloys at room temperature were studied and correlated with the previously characterized microstructures. All the alloys showed multiphase microstructures with major α-Al dendritic matrix reinforced with secondary phases. In terms of mechanical properties, the developed alloys exhibited a high compression yield strength up to 420 MPa, high compression fracture strength up to 563 MPa, and elongation greater than 12%.

The aim of this work is to study the microstructure of four high entropy alloys (HEAs) produced by large scale vacuum die casting.

This work aims to calculate the rigidity point temperature of aluminum alloys by three new methods and compare them with currently employed methods. The influence of major and minor alloying elements over the rigidity point temperature is also discussed. Until now it has been difficult to determine the exact temperature of the rigidity point, since small variations in the data obtained give variable results, making it difficult to automate the process with high accuracy. In this work we suggested three new mathematic methods based on the calculation of higher order derivatives of (dT/dt) with respect to time or temperature compared to those currently employed. A design of experiments based on the Taguchi method was employed to compare the effect of the major and minor alloying elements for the AlSi10Mg alloy, and to evaluate the accuracy of each developed method. Therefore, these systems will allow better automation of rigidity point temperature (RPT) determination, which is one of the most important solidification parameters for solidification simulators. The importance of the correct determination of this parameter lies in its relation to quality problems related to solidification, such as hot tearing. If the RPT presents very low-temperature values, the aluminum casting will be more sensitive to hot tearing, promoting the presence of cracks during the solidification process. This is why it is so important to correctly determine the temperature of the RPT. An adequate design of chemical composition by applying the methodology and the novel methods proposed in this work, and also the optimization of process parameters of the whole casting process with the help of the integrated computational modeling, will certainly help to decrease any internal defective by predicting one of the most important defects present in the aluminum industry.