Abstract
The global transition to clean energy technologies has escalated the demand for lithium (Li), a critical component in rechargeable Li-ion batteries, highlighting the urgent need for efficient and sustainable Li(+) extraction methods. Nanofiltration (NF)-based separations have emerged as a promising solution, offering selective separation capabilities that could advance resource extraction and recovery. However, an NF-based lithium extraction process differs significantly from conventional water treatment, necessitating a paradigm shift in membrane materials design, performance evaluation metrics, and process optimization. In this review, we first explore the state-of-the-art strategies for NF membrane modifications. Machine learning was employed to identify key parameters influencing Li(+) extraction efficiency, enabling the rational design of high-performance membranes. We then delve into the evolution of performance evaluation metrics, transitioning from the traditional permeance-selectivity trade-off to a more relevant focus on Li(+) purity and recovery balance. A system-scale analysis considering specific energy consumption, flux distribution uniformity, and system-scale Li(+) recovery and purity is presented. The review also examines process integration and synergistic combinations of NF with emerging technologies, such as capacitive deionization. Techno-economic and lifecycle assessments are also discussed to provide insights into the economic viability and environmental sustainability of NF-based Li(+) extraction. Finally, we highlight future research directions to bridge the gap between fundamental research and practical applications, aiming to accelerate the development of sustainable and cost-effective Li(+) extraction methods.