Model-based design and optimisation of hydrometallurgical liquid–liquid extraction processes

Abstract

Hydrometallurgical methods are suitable for the treatment of primary, secondary, highand low-grade raw materials enabling the production of metals essential to modern society, in an environmentally and economically sustainable way. Among other methods, liquid–liquid extraction is widely used in the processing of various base, precious and other metals due to the development of stable selective extractants that effectively recover valuable metals from complex raw materials. The increasing demands for pure metals and environmentally sustainable processes further promote the development of liquid–liquid extraction as a separation technique.

The purpose of the studies presented in this thesis is to develop tools, which can help to decrease costs and improve the efficiency of process development in hydrometallurgy. Since modelling and simulation can be used effectively in the development of processes for production of metals, the application of modelling and simulation tools to hydrometallurgical process development is explored in the current thesis. The fields: model formulation, efficient solution of model equations, simulation of counter-current liquid–liquid extraction cascades as well as automated process synthesis in hydrometallurgy are studied. Mechanistic modelling is applied to simulate liquid–liquid extraction processes, whereas a metaheuristic algorithm is implemented in order to perform the efficient automated synthesis of the hydrometallurgical processes.

Mechanistic models are based on the chemistry of the separation processes and provide detailed information on their thermodynamic and kinetic limitations. Also they can serve as a tool for determining the optimal configuration of a metal’s recovery process. The research on mechanistic modelling and process simulation was focused on two cases, for which the equilibrium models were developed. The first one was the efficiency improvement of copper liquid–liquid extraction by studying the factors affecting the copper extraction and the fate of iron as the main impurity in the process. New experimental data on the extraction equilibrium of copper and iron in the extraction and stripping steps were collected. The data were used to validate the developed model. It was found that the high copper loading of the organic phase in the extraction stages leads to decreased iron co–extraction and, consequently, higher process efficiency. The developed simulation tool helps quantify the effect.

The second case was devoted to the analysis of the operation and performance of a liquid–liquid extraction process for fractionation of cobalt, nickel, and lithium from Li–ion battery leachates of different composition. The process model was developed and validated using data taken from literature. A simple and effective process flowsheet, in which cobalt and nickel were first selectively extracted, yielding pure lithium raffinate, and then separated as pure products in the stripping steps, was thoroughly studied and optimized using numerical simulation. The process was found to be able to separate cobalt, nickel, and lithium from leachates of different composition in a single extraction circuit. Furthermore, the operation of the process is rather flexible, and pure fractions (>99%) of lithium, nickel, and cobalt may be produced with high yield.

Advanced mathematical and statistical methods were employed to ensure confidence in the modelling and simulation results. The mechanistic models of extraction equilibrium were solved by the rate-based approach, which provides fast calculations with controlled accuracy. Nonlinear regression analysis was used to estimate the values of the model parameters. A Markov chain Monte Carlo algorithm was used to assess the reliability of the modelling results. The sequential-modular approach was used for simulation of counter-current operation of the liquid–liquid extraction processes.

A method for the automated synthesis of hydrometallurgical processes using limited amounts of experimental data was developed. The method allows the selection and sequencing of the most effective process step options (e.g., leaching, liquid–liquid extraction, and precipitation) and simultaneously optimising their performance. An algorithm based on the Ant colony optimisation technique was used to generate promising process alternatives and identify the most economic one in an iterative manner. Key performance indicators were employed to compare the process alternatives. The applicability of the method was studied by investigating zinc recovery from argon oxygen decarburisation dust and the recovery of lanthanides from nickel metal hydride batteries. The processes for the recovery of the valuable components were successfully synthesised, and recommendations for further improvements of the processes were given.