Assessing the Techno-Economic Feasibility of Solvent-Based, Critical Material Recovery from Uncertain, End-of-Life Battery Feedstock
As emerging technologies drive up demand for rare earths, value recovery from recycling end-of-life products provides an option for partially closing the material loop, conserving natural capital and enhancing resource security. Yet the techno-economic feasibility of recycling depends on uncertainties associated with the feed input to the recovery process, and the effect of these uncertainties on the viability of the recycling facility. In this study, we couple a first-principle solvent extraction model with an economic model for a separation facility and apply it to assess byproduct recovery and rare earth separation from spent nickel-metal hydride batteries, illustrating the significance of parametric uncertainties. The study shows the importance of risk-informed decision making in the investment, design, and operation of recycling facilities.
KeywordsRare earth Critical material recovery NiMH battery recycling Solvent extraction Stochastic optimization Uncertainty analysis Gibbs energy minimization
We wish to acknowledge Allinson Santos-Xavier (Argonne National Lab) for providing valuable discussions on optimization approaches. The submitted manuscript has been created by UChicago Argonne LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne National Laboratory’s work was supported by the US Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), under contract DE-AC02-06CH11357. The US government retains for itself, and others acting on its behalf, a paid-up non-exclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the government. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility.
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