Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries

Anna Vanderbruggen*, Eligiusz Gugala, Rosie Blannin, Kai Bachmann, Rodrigo Serna-Guerrero, Martin Rudolph

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)
115 Downloads (Pure)


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.

Original languageEnglish
Article number106924
Number of pages14
JournalMinerals Engineering
Early online date27 May 2021
Publication statusPublished - 1 Aug 2021
MoE publication typeA1 Journal article-refereed


  • Automated mineralogy
  • Black mass
  • Characterization
  • Liberation
  • Lithium-ion batteries
  • Mineral processing
  • Recycling


Dive into the research topics of 'Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries'. Together they form a unique fingerprint.

Cite this