The Development of a Statistical Model to Predict the Recovery of Cobalt, Nickel, and Manganese from Spent Lithium-Ion Batteries via Reverse Flotation

The growing production of lithium-ion batteries is leading to an increase in waste, which contains elements considered critical in industry, like cobalt, manganese and nickel. Urban mining offers an opportunity to recover these elements and reintroduce them into the value chain. This study aimed to detect and recover metals of interest present in discarded lithium-ion batteries and determine the influence of flotation operating parameters on the recovery of the detected elements through an experimental design. The batteries subjected to the flotation experiments were obtained from various types of common disused mobile devices. They were dismantled by separating the copper sheets from the anode and the aluminum sheets from the cathode, to be subjected to a comminution process and elemental composition analysis using X-ray fluorescence. Only the cathode components were subjected to flotation. The flotation process was carried out by controlling the level of agitation and aeration and the flotation time using an automated flotation cell. The experiments were configured in a 23 experimental design. Average recoveries of approximately 67% for cobalt, 64% for manganese, and 63% for nickel were achieved at a pH of 12.5 and a pulp density of 3.33 g/L using MIBC as the sole reagent. Statistical analysis at a 95% confidence level identified agitation, aeration, and flotation time both individually and in combination as significant factors. Linear models were developed to predict metal recovery, showing good agreement with experimental data (errors < 10%; standard deviation < 3%).