Metal-organic framework membranes for lithium extraction from Mg/Li brines: Advances in design, machine learning-driven optimization, and scalability challenges

Abstract

Lithium extraction from high Mg/Li ratio salt-lake brines remains a critical challenge due to the inherent trade-off between membrane permeability and selectivity. Traditional nanofiltration membranes struggle to achieve efficient separation of Li⁺ and Mg²⁺, particularly in harsh saline environments. This review highlights the transformative potential of metal–organic framework (MOF)-based membranes, which leverage tunable pore sizes, functionalized surfaces, and synergistic separation mechanisms (e.g., size exclusion, electrostatic repulsion) to overcome these limitations. We systematically analyze MOF synthesis strategies, membrane design principles, and machine learning-driven material screening to optimize performance. Innovations such as sub-nanometer pore engineering, hybrid organic–inorganic architectures, and stability-enhancing modifications are emphasized. Furthermore, we discuss the integration of computational tools and high-throughput simulations to accelerate the discovery of high-performance membranes. Despite progress, challenges in scalability, long-term stability, and industrial adaptability persist, underscoring the need for interdisciplinary approaches to bridge laboratory advancements with real-world applications.