Smart design of sustainable polymer-based membrane materials for lithium recovery

Metal and mineral resources are essential for electrification, renewable energy, and advanced computing. The U.S. lists 50 strategic minerals—including lithium, cobalt, nickel, and rare earth elements (REEs)—as vital to energy security and economic stability. Lithium and cobalt demand, driven mainly by EV batteries, is rising sharply. REEs are crucial for EV motors and wind turbines. The U.S., UK, and EU are investing to secure domestic supply chains.

The surge in global demand for lithium-ion batteries highlights the urgent need to expand lithium recycling and develop extraction from unconventional sources. Conventional methods, such as hard rock mining, face environmental and scalability constraints. Direct lithium extraction (DLE) from aqueous resources—including salt-lake brines and geothermal fluids—offers a promising alternative by improving efficiency, reducing ecological impacts, and enhancing economic viability. A wide range of DLE approaches has been explored, including sorbents and membrane-based separation processes. Among these, membrane technologies offer unique advantages: modular scalability, reduced reliance on harmful reagents, adaptability to variable feed compositions, and the ability to fractionate input streams. While nanofiltration (NF) and ion-exchange (IEX) membranes can discriminate ions by size and valence, their performance in multicomponent feeds remains poorly understood—a key barrier to industrial deployment. Mechanistic models capturing NF and IEX behavior in complex systems are needed to identify suitable applications and guide the design of next-generation selective and robust membranes.

This project will develop universally lithium-selective polymer-based membranes through bottom-up molecular design to process-scale modelling, enabling efficient lithium recovery across diverse feed compositions and operating conditions.

We are seeking candidates with a BSc or Master’s degree in Chemical Engineering, Chemistry, or Materials Science, who have a strong interest in developing a career in materials design using computational techniques. Applicants should demonstrate good skills in computational modelling, ideally with prior experience in coding (e.g. Python, MATLAB, or Fortran). Candidates must also meet the minimum entry requirements for our PhD programme.

Open to candidates who pay UK/home rate fees. See UKCISA for further information.