Investigating Recycled Battery Materials using a Range of Analytical Methods

C. Stephan, K. Evans
PerkinElmer Inc,
Canada

Keywords: Lithium Battery Recycling, Lithium Circular Economy

Summary:

The process of recycling lithium-ion batteries has received some attention over the past few years due to the increase demand for raw materials in this area. The increased demand is largely as a result of an increased demand for electric vehicles and other e-mobility which may eventually outstrip the supply of raw materials from natural sources. As recycled materials begin to contribute a large share to the pool of raw materials available for battery recycling, having the tools to better understand and optimize the recycling process and final products will become more important. This work aims to give a high-level overview of how already available analytical techniques, such as inductively coupled plasma-mass spectrometry (ICP-MS) and thermogravimetric analysis coupled to infrared spectroscopy (TG-IR) can be implemented to gain valuable insights about recycled materials. The first section will demonstrate the use of ICP-MS to determine impurities in two important potential final products of battery recycling, lithium carbonate and lithium hydroxide. As is the case when virgin raw materials are use, certain impurities must be below pre-defined limits to ensure good performance, safety, and longevity in the battery. The next section will look at the simultaneous identification and quantification of residual electrolyte in black mass produced from the battery recycling process. TGA allows for a sample to be heated and the weight loss to be measured as a function of temperature therefore providing quantitative information. IR spectroscopy may be used to identify the evolved gas and therefore elucidate the structure of the material that has decomposed or evaporated. The presentation will demonstrate the sample preparation and analysis of different materials found throughout the battery recycling value chain and establish best practices for data collection and interpretation.