Editors: | F. Kongoli, S.V. Alexandrovich, D.V. Grigorievich, L.L. Igoryevich, I. Startsev, T.A. Vladimirovich |
Publisher: | Flogen Star OUTREACH |
Publication Year: | 2019 |
Pages: | 193 pages |
ISBN: | 978-1-989820-03-2 |
ISSN: | 2291-1227 (Metals and Materials Processing in a Clean Environment Series) |
The selective recovery of valuable metals from metal-containing residues not only conserves the primary resources, but also improves the availability of raw materials. First and foremost, the focus must be kept on previously unrecycled wastes as these have been removed from the circular resource flow.
The recycling of used batteries effects not only the treatment of hazardous waste, but also the recovery of valuable elements used in this field. On the commonly used pyrometallurgical route, mostly only the main metals are recovered. The application of hydrometallurgy remedies this problem and is mentioned in various research papers [1]. This process route gives the possibility of recycling for materials such as rare earths, cobalt and nickel which are often slagged in the pyrometallurgical process [2]. The recycling of metal-containing residues from the battery sector by hydrometallurgical means offers a wide range of possibilities. It is assumed that many different residues, as well as nickel-cadmium or nickel-metal hydride batteries and lithium-ion batteries can be recycled. Recycling processes for these metal-containing residues are divided in chemical processes (leaching, selective precipitation, solvent extraction) and mechanical and/or thermal processes [2,3].
The optimization of leaching parameters in the field of recycling of metal-containing residues represents a complex topic in the literature. In addition to the selection of an appropriate leaching medium, the variation of different leaching parameters such as temperature, time, solid-liquid ratio and concentration of the leaching medium have to be investigated in order to obtain the best possible result. Efficient leaching can only occur if there is an optimized process window with upper and lower limits for the respective parameters [4]. For experimental design and evaluation, a statistical software for design of experiments based on a fully factorial model serves for the interpretation of the process area [5].