A Kinetic Study on the Preparation of Al-Mn Alloys by Aluminothermic Reduction of Mn₃O₄ and MnO Powders

The study of aluminothermic reduction in manganese compounds is a complex challenge in preparing Al-Mn alloys. The primary objective of this study was to ascertain the activation energy values for the aluminothermic reduction of MnO and Mn3O4 oxides derived from alkaline batteries. The study melted aluminum found in beverage cans and utilized the technique of powder addition with mechanical agitation. The kinetics of the reaction were studied under the effects of temperature (750, 800, and 850 °C), degree of agitation (200, 250, and 300 rpm), and the initial concentration of magnesium in molten aluminum (1, 2, 3, and 4% by weight). Kinetic measurements for Mn3O4 particles suggest a reaction mechanism that occurs in stages, where manganese undergoes oxidation states [Mn+3] to [Mn+2] until it reaches the oxidation state Mn0, which allows it to dissolve in the molten aluminum, forming alloys with up to 1.5 wt.% of Mn. Therefore, the kinetic of the aluminothermic reduction of MnO is described by the geometric contraction model, while the mechanism of Mn3O4 reduction occurs in two stages: geometric contraction, followed by an additional stage involving the diffusion of chemical species to the boundary layer. In addition, this stage can be considered a competition between the formation of MnO and the chemical reaction itself

Mathematical modelling for furnace design refining molten aluminum

The design of an aluminium melting furnace has faced two challenges: mathematical modelling and simulative optimization. This paper first uses fluid dynamics to model the aluminium process mathematically. Then, the model is utilized to simulate a round shaped reverberatory furnace for melting aluminium alloys. In order to achieve the highest thermal efficiency of the furnace, modelling and simulation are performed to predict complex flow patterns, geometries, temperature profiles of the mixture-gas air through the main chamber, as well as the melting tower attached to the furnace. The results led to the establishment of optimal position and angle of the burner, which are validated through physical experiments, ensuring recirculation of the combustion gases through the melting chamber and the melting tower. Furthermore, a proper arrangement of refractory materials is derived to avoid heat losses through the outer surface of the furnace. Temperature profiles are also determined for the optimization to arrive at the final design of the furnace. Compared with manual designs previously practiced, the simulation-based optimal design of furnaces offers excellent guidance, an increase in the aluminium processing and magnesium removal for more refined alloys, and an increased processing rate of aluminium chip accession