| Title | Multicomponent solvent extraction modelling of lithium, cobalt, nickel, and manganese from simulated black mass leachate |
|---|---|
| ID_Doc | 13445 |
| Authors | Lu, JN; Li, W; Stevens, GW; Mumford, KA |
| Title | Multicomponent solvent extraction modelling of lithium, cobalt, nickel, and manganese from simulated black mass leachate |
| Year | 2024 |
| Published | |
| Abstract | The role of lithium-ion batteries in facilitating the global shift towards renewable energy is paramount. Managing the responsible lifecycle of these batteries, including their disposal and recycling at the end of their operational life, holds considerable importance. These practices not only mitigate the environmental impact but also address the supply vulnerability of battery metals sourced from primary natural reserves. The major compositions of batteries, notably lithium, nickel, and cobalt, are typically concentrated within a material known as black mass, a vital commodity in the battery recycling sector. Solvent extraction is a proficient method for the simultaneous recovery of these materials, to produce a feedstock for new battery manufacturing, aligning with the principles of a circular economy. The separation and purification of these metals, while still challenging, are comparatively less difficult than the requirement posed by primary resource extraction. The co-extraction of multiple compositions in a single step holds tremendous potential for reducing the cost associated with the separation process. Nevertheless, this approach is an unconventional solvent extraction method, necessitating advanced multicomponent extraction models. The present study employed the equilibrium status iteration (ESI) model to describe and predict the extraction performance of battery metals in aqueous solutions. This model is instrumental to the design and optimisation of scaled-up solvent extraction facilities. To illustrate the model, ESI was applied to resolve equilibrium data related to a three-stage counter-current extraction scheme. This removes the laborious trial-and-error phase of experimental inquiry when designing the process involving multiple target metals. |
| https://doi.org/10.1016/j.seppur.2023.126181 |
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