Synthesis of hydrometallurgical processes for valorization of secondary raw materials using ant colony optimization and key performance indicators

Abstract

An algorithm-based method for synthesis of hydrometallurgical processes using limited amounts of experimental data is presented. The method enables simultaneous selection and sequencing of unit operations and optimization of operating parameters. An ant colony optimization (ACO) based algorithm is used to identify the most economic process alternative in an iterative manner. Key performance indicators are used for comparison of candidate processes: a purification performance index measures purity improvement and a separation cost indicator is used as an objective function in process optimization. Computational times were reduced significantly with the suggested method compared to an algorithm which evaluates all the possible process options. The practical applicability of the method to hydrometallurgy is demonstrated by investigating zinc recovery from argon oxygen decarburization dust with two alternative leaching methods and recovery of lanthanides from nickel metal hydride (NiMH) batteries. In the first zinc recovery process, 150 min normal batch leaching with 0.5 M H2SO4 is used, and in the other one 270 min batch leaching with H2SO4 is done by controlling the pH (> 3.0). In both cases the leachate is extracted with D2EHPA at pH 4.27, and stripped with circulating solution from zinc electrolysis. For lanthanides recovery the algorithm suggested a process in which the raw material is leached with 1.3 M HCl, the leachate is extracted with D2EHPA at pH 2.2, organic phase is stripped with 2.0 M HCl and 99% pure Ln-oxalates are precipitated with oxalic acid at pH 0.6. Compared to previously suggested process for the same raw material, the algorithm suggests operating the leaching step such that higher selectivity is achieved by sacrificing some yield.