In ores, chalcopyrite is usually associated with other sulfide minerals, such as sphalerite, galena, and pyrite, in a dispersed form, with complex mineralogical structures. Concentrates obtained by flotation of such ores are unsuitable for pyrometallurgical processing owing to their poor quality and low metal recovery. This paper presents the leaching of chalcopyrite concentrate from the location “Rudnik, Serbia”. The samples from the flotation plant were treated with hydrogen peroxide in sulfuric acid. The influences of temperature, particle size, stirring speed, as well as the concentrations of hydrogen peroxide and sulfuric acid were followed and discussed. Hence, the main objective was to optimize the relevant conditions and to determine the reaction kinetics. It was remarked that the increase in temperature, hydrogen peroxide content, and sulfuric acid concentration, as well as the decrease in particle size and stirring speed, contribute to the dissolution of chalcopyrite. The dissolution kinetics follow a model controlled by diffusion, and the lixiviant diffusion controls the rate of reaction through the sulfur layer. Finally, the main characterization methods used to corroborate the obtained results were X-ray diffraction (XRD) as well as qualitative and quantitative light microscopy of the chalcopyrite concentrate samples and the leach residue.

Titanium alloys have been present for decades as the main components for the production of various orthopedic and dental elements. However, modern times require titanium alloys with a low Young’s modulus, and without the presence of cytotoxic alloying elements. Machine learning was used with aim to analyze biocompatible titanium alloys and predict the composition of Ti alloys with a low Young’s modulus. A database was created using experimental data for alloy composition, Young’s modulus, and mechanical and thermal properties of biocompatible titanium alloys. The Extra Tree Regression model was built to predict the Young’s modulus of titanium alloys. By processing data of 246 alloys, the specific heat was discovered to be the most influential parameter that contributes to the lowering of the Young’s modulus of titanium alloys. Further, the Monte Carlo method was used to predict the composition of future alloys with the desired properties. Simulation results of ten million samples, with predefined conditions for obtaining titanium alloys with a Young’s modulus lower than 70 GPa, show that it is possible to obtain several multicomponent alloys, consisting of five main elements: titanium, zirconium, tin, manganese and niobium.

The influence of the multi-stage electrostatic separation (ESS) of mechanically treated and magnetically separated waste electronic material and the pyrolysis of the selected ESS fraction on the distribution of metal elements (MEs), elements contained in refractory oxides (EROs), bromine (Br), and rare-earth elements (REEs) contained in waste electronic material was studied. The concentration of MEs, Br, and EROs in the tested samples was determined by X-ray fluorescence analysis, and the concentration of REEs and uranium was determined by inductively coupled plasma mass spectrometry (ICP-MS). The analysis of the distribution of elements during the multi-stage ESS showed that MEs were predominantly distributed in the conductive fraction and Br, EROs, and REEs were distributed in the nonconductive fraction. The nonconductive fraction (NC2) of the two-stage ESS was subjected to a low-temperature vacuum pyrolysis (T = 550 °C, p = 10 mbar). The distribution of pyrolysis products of the NC2 fraction was determined. The main products of the vacuum pyrolysis experiments were the solid residue phase (54.4 wt.%) and oils (35.4 wt.%). It has been proven that pyrolysis can significantly increase the concentration of MEs, EROs, and REEs in raw materials, thereby providing a method for cost-effectively obtaining of REEs from waste printed circuit boards.