(456d) Process Systems Engineering Enables Efficient and Sustainable Membrane-Based Critical Material Separations

The modern world has become reliant on critical materials (e.g., lithium, magnesium, neodymium) denoted by the importance of their supply to national security.¹ These critical minerals (CMs) are used in various technology applications. For example, lithium, cobalt, and nickel are used in batteries; neodymium and dysprosium are used for permanent magnets; and gadolinium and lutetium are used for medical imaging.¹ As demand for CMs grows, there is interest in developing sustainable and resilient processes for CM production, ultimately aiming to promote a circular economy. This presentation will first present a systematic review of the current state of CM processing, which illustrates that membranes are well-positioned to tackle emerging challenges in CM processing and can efficiently address diverse separation needs with the help of process systems engineering techniques. The second half of the presentation will highlight ongoing membrane modeling efforts and present a preliminary costing model and environmental analysis.

The current separation infrastructure for CMs has a significant environmental impact and cannot rapidly respond to fluctuating market conditions. With the higher quality (i.e., high concentration, easily extractable) ores having already been exploited, the quality of primary ores is declining.² Therefore, there is growing interest in harvesting CMs from unconventional sources, such as recycled electronics and industrial waste products, and reducing the cost and impact of recycling CM-intensive products. For example, recycling lithium-ion batteries (LIBs) is of great interest, as the accumulation of spent LIBs is expected to grow with the rise of electric vehicles, and the concentration of lithium within these spent LIBs is approaching that of the primary ore.³ Current CM production and processing pathways have substantial room for improvement in performance and face many potential challenges when applied to unconventional feedstocks. For example, the traditional method of producing high purity, individually separated rare earth elements (i.e., solvent extraction) generally needs to be operated at a steady state and is susceptible to perturbations, which could be exacerbated by day-to-day changes in feedstock compositions of some unconventional resources being explored. Further, the current processing methods of CMs are resource intensive. For example, hydrometallurgical processes, which include leaching, solvent extraction, and precipitation, require harsh chemicals and large footprints, and pyrometallurgical processes require high temperatures.^3,4 In this contribution, we argue that membranes can be leveraged within these traditional pathways to reduce the need for chemical reagents, decrease footprints, and lower energy demand. These process intensification benefits have been demonstrated in other fields (e.g., carbon capture^5,6) and can similarly be applied here to enhance CM separations, especially in terms of process flexibility and cost reductions due to their modular design.

Although there are expected challenges in applying membrane separations within CM processing, such as the vast design space and material property limits,⁷ process systems engineering can be leveraged to tackle these challenges and efficiently optimize membrane systems. For example, a multi-scale optimization framework has been used to understand how material-scale properties impact process-level separations.⁸ Most notably, superstructure optimization of diafiltration cascades has demonstrated the process-scale feasibility of membrane separations for lithium-cobalt solutions.⁹ These preliminary results support our efforts to develop more robust membrane models at large scales. For example, the membrane system in Wamble et al.⁹ uses a constant sieving coefficient to calculate the fraction of ions that permeate through the membrane. In reality, the transport phenomena are much more complicated. For example, the Donnan Steric Pore Model with Dielectric Exclusion (DSPM-DE) is a well-known model to describe the transport (i.e., diffusion, convection, and electromigration) and exclusion (i.e., steric, dielectric, and Donnan) mechanisms during nanofiltration of electrolytes.¹⁰ However, as the complexity of the mathematical model increases, the optimization model becomes more computationally expensive. Therefore, we first investigate modifications to the sieving coefficient model, such as accounting for concentration polarization. Further, optimizing separations for representative feeds is essential, meaning we must accurately model multi-component solutions to describe realistic CM feeds (e.g., salt-lake brines can contain several ions, such as lithium, magnesium, sodium, potassium, and calcium).¹⁰ Finally, we propose a preliminary costing model to include both technical and economic objectives in the membrane model optimization formulation.

References

(1) Burton, J. U.S. Geological Survey Releases 2022 List of Critical Minerals. https://www.usgs.gov/news/national-news-release/us-geological-survey-rel... (accessed 2023-07-19).

(2) Lair, L.; Ouimet, J. A.; Dougher, M.; Boudouris, B. W.; Dowling, A. W.; Phillip, W. A. Critical Mineral Separations: Opportunities for Membrane Materials and Processes to Advance Sustainable Economies and Secure Supplies. Annu Rev Chem Biomol Eng 2024. [Accepted]

(3) Liu, C.; Lin, J.; Cao, H.; Zhang, Y.; Sun, Z. Recycling of Spent Lithium-Ion Batteries in View of Lithium Recovery: A Critical Review. Journal of Cleaner Production. Elsevier Ltd August 10, 2019, pp 801–813. https://doi.org/10.1016/j.jclepro.2019.04.304.

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(6) Ramezani, R.; Randon, A.; Felice, L. Di; Gallucci, F. Using a Superstructure Approach for Techno-Economic Analysis of Membrane Processes. Chemical Engineering Research and Design 2023, 199, 296–311. https://doi.org/10.1016/j.cherd.2023.10.007.

(7) Yin, H.; Xu, M.; Luo, Z.; Bi, X.; Li, J.; Zhang, S.; Wang, X. Machine Learning for Membrane Design and Discovery. Green Energy and Environment. KeAi Publishing Communications Ltd. 2022. https://doi.org/10.1016/j.gee.2022.12.001.

(8) Eugene, E. A.; Phillip, W. A.; Dowling, A. W. Material Property Targets to Enable Adsorptive Water Treatment and Resource Recovery Systems. ACS ES&T Engineering 2021, 1 (8), 1171–1182. https://doi.org/10.1021/acsestengg.0c00046.

(9) Wamble, N. P.; Eugene, E. A.; Phillip, W. A.; Dowling, A. W. Optimal Diafiltration Membrane Cascades Enable Green Recycling of Spent Lithium-Ion Batteries. ACS Sustain Chem Eng 2022, 10 (37), 12207–12225. https://doi.org/10.1021/acssuschemeng.2c02862.

(10) Foo, Z. H.; Rehman, D.; Bouma, A. T.; Monsalvo, S.; Lienhard, J. H. Lithium Concentration from Salt-Lake Brine by Donnan-Enhanced Nanofiltration. Environ Sci Technol 2023, 57 (15), 6320–6330. https://doi.org/10.1021/acs.est.2c08584.

Acknowledgements: This effort was funded by the U.S. Department of Energy’s Process Optimization and Modeling for Minerals Sustainability (PrOMMiS) Initiative, supported by the Office of Fossil Energy and Carbon Management’s Office of Resource Sustainability.

Disclaimer: This project was funded by the Department of Energy, National Energy Technology Laboratory an agency of the United States Government, through a support contract. Neither the United States Government nor any agency thereof, nor any of its employees, nor the support contractor, nor any of their employees, makes any warranty, expressor implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or any of their contractors