Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries. (1st August 2021)

• Record Type: Journal Article
• Authors: Vanderbruggen, Anna; Gugala, Eligiusz; Blannin, Rosie; Bachmann, Kai; Serna-Guerrero, Rodrigo; Rudolph, Martin
• Is Part Of: Minerals engineering. Volume 169(2021)
• Publication Date: 2021-08-01
• Subjects: Automated mineralogy -- Black mass -- Characterization -- Liberation -- Lithium-ion batteries -- Recycling -- Mineral processing; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Mines and mineral resources; Periodicals; Electronic journals; 622
• DOI: 10.1016/j.mineng.2021.106924
• Languages: English
• ISSNs: 0892-6875

Abstract

Highlights: Introduced automated mineralogy to lithium ion battery recycling. Successful identification and quantification of lithium ion battery components. Estimation of the liberation degree of the lithium ion battery components. Different liberation behaviour of Al foil and Cu foil during thermo-mechanical process. Developed scripts to quantify the different lithium metal oxide chemistry. Abstract: Mechanical recycling processes aim to separate particles based on their physical properties, such as size, shape and density, and physico-chemical surface properties, such as wettability. Secondary materials, including electronic waste, are highly complex and heterogeneous, which complicates recycling processes. In order to improve recycling efficiency, characterization of both recycling process feed materials and intermediate products is crucial. Textural characteristics of particles in waste mixtures cannot be determined by conventional characterization techniques, such as X-ray fluorescence and X-ray diffraction spectroscopy. This paper presents the application of automated mineralogy as an analytical tool, capable of describing discrete particle characteristics for monitoring and diagnosis of lithium ion battery (LIB) recycling approaches. Automated mineralogy, which is well established for the analysis of primary raw materials but has not yet been tested on battery waste, enables the acquisition of textural and chemical information, such as elemental and phase composition, morphology, association and degree of liberation. For this study, a thermo-mechanically processed black mass (<1 mm fraction) from spent LIBs was characterized with automated mineralogy. Each particle was categorized based on which LIB component it comprised: Al foil, Cu foil, graphite, lithium metal oxides and alloys from casing. A more selective liberation of the anode components was achieved by thermo-mechanical treatment, in comparison to the cathode components. Therefore, automated mineralogy can provide vital information for understanding the properties of black mass particles, which determine the success of mechanical recycling processes. The introduced methodology is not limited to the presented case study and is applicable for the optimization of different separation unit operations in recycling of waste electronics and batteries.