Assessment of Silicon and Rhenium Recovery Efficiency from Copper-Containing Tailings of Processing Plants
Karimova L. Makasheva G. Kharchenko Y. Magaz A.
April 2025Multidisciplinary Digital Publishing Institute (MDPI)
Eng
2025#6Issue 4
In the face of the global depletion of natural resources and increasing demand for sustainable development, processing industrial waste, such as tailings from processing plants, is becoming essential. This study focuses on combined processing technologies, including flotation concentration and concentrate processing, allowing the efficient recovery of valuable components. This study aims to investigate the possibility of thermochemical enrichment and the opening of low-grade copper tailings of processing plants with the transfer of silicon and rhenium in the form of silicate-ions and perrhenate-ions into a solution with the output of a multifactor multiplicative model and obtaining tabular nomograms. Multifactor experiments on the thermochemical enrichment of rough copper concentrates made it possible to construct partial dependences of silicon and rhenium extraction into a solution and to obtain multiplicative Protodyakonov–Malyshev models of these processes and multifactor nomograms over a wide range of temperatures, durations, and alkali-to-concentrate ratios to determine the maximum recovery rates. The developed multifactor models made it possible to establish the optimal intervals of changes in the concentrate sintering parameters, providing high recovery rates (over 85% of silicon and 98% of rhenium) during subsequent water leaching. Optimal sintering conditions (temperature of 350 °C, the duration of 90 min, and the ratio of NaOH to concentrate = 1:2) ensured a recovery of up to 85% of silicon and 98% of rhenium from the concentrate into the solution. This recovery rate reduces the need for primary raw materials and positively affects the production’s environmental performance because it minimizes the amount of industrial waste disposal.
concentrate , final tailings , mathematical models , multiple correlation analysis , recovery , rhenium , silicon , sintering
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Metallurgy Laboratory of LLP “Innovation”, Karaganda, 100024, Kazakhstan
LLP “KazHydroMed”, Karaganda, 100000, Kazakhstan
Department of Metallurgy and Materials Science, Non-Profit Joint Stock Company “Karaganda Industrial University”, Temirtau, 101400, Kazakhstan
Metallurgy Laboratory of LLP “Innovation”
LLP “KazHydroMed”
Department of Metallurgy and Materials Science
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