Protocol for designing, optimizing, and analyzing reverse supply chains using RELOG.

In this protocol, we describe the use of RELOG, an open-source, supply chain optimization package, for robust design and analysis of optimal reverse logistics and manufacturing networks. We detail installation steps and input data assembly, followed by problem modeling. We further detail how to run the RELOG optimization, visualize, and analyze the results. The implementation discussed here illustrates battery recycling; however, our package can analyze a wide variety of supply chains with multiple types of plants, products, and time periods. For complete details on the use and execution of this protocol, please refer to Xavier and Iloeje (2020)1 and Iloeje et al. (2022).2.

A systematic analysis of the costs and environmental impacts of critical materials recovery from hybrid electric vehicle batteries in the U.S.

Critical materials such as rare earth underpin technologies needed for a decarbonized global economy. Recycling can mitigate the supply risks created by the increasing demand and net import dependence, and enable a circular economy for critical materials. In this study, we analyze the feasibility and life-cycle impacts of recovering critical materials from spent nickel metal hydride batteries from hybrid electric vehicles in the U.S., accounting for stocks, battery scrappage, and end-of-life reverse logistics, given uncertain future availability scenarios. Our results show that the total collection and recycling costs depend strongly on future battery availability, with marginal costs exceeding marginal revenues when the availability of spent batteries declines. We quantify the potential of recycling to reduce primary imports, as well as the accompanying climate change and resource impacts. We explore the underlying reverse logistics infrastructure required for battery recycling and evaluate strategies for reducing associated capital investment risk.

Gibbs Energy Minimization Model for Solvent Extraction with Application to Rare-Earths Recovery.

The emergence of technologies in which rare-earth elements provide critical functionality has increased the demand for these materials, with important implications for supply security. Recycling provides an option for mitigating supply risk and for creating economic value from the resale of recovered materials. While solvent extraction is a proven technology for rare-earth recovery and separation, its application often requires extensive trial-and-error experimentation to estimate parameter values and determine experimental design configurations. We describe a modeling strategy based on Gibbs energy minimization that incorporates parameter estimation for required thermodynamic properties as well as process design for solvent extraction and illustrate its applicability to rare earths separation. Visualization analysis during parameter estimation revealed a linear relationship between the standard enthalpies of the extractant and respective organo-metal complexes, analogous to the additivity principle for predicting molar volumes of organic compounds. Establishing this relationship reduced the size of the parameter estimation problem and yielded good agreement between model predictions and reported equilibrium extraction data, validating the property estimates for the organic phase species. Design exploration and optimization results map the space of feasible solvent extraction column configurations and identify the set of optimal design parameter values that meet recovery and purity targets.