AI-assisted advanced seawater desalination membranes for supporting offshore green hydrogen production

Green hydrogen production offshore, utilizing renewable energy, addresses water scarcity and supports low-carbon energy transition. Expanding offshore green power capacity enhances integrated desalination-electrolysis systems, boosting market demand. Membrane separation technology offers advantages of no phase change, high efficiency, and low energy consumption, yet traditional methods remain inefficient and costly. Here, we examine the latest advances in artificial intelligence (AI)-driven membrane technologies, focusing on AI's advantages in membrane structure design, process optimization, performance prediction, and engineering applications. Representative studies demonstrate the potential of AI-assisted membrane development: inverse-designed nanoporous membranes achieved water transport rates approximately twice those of boric acid, while AI-screened membrane materials showed theoretical desalination efficiencies approaching 100%. In addition, NF90-based seawater purification has enabled hydrogen production rates of approximately 240-270 μmol cm −2 h −1 . At the process level, AI-assisted multi-objective optimization has achieved prediction coefficients of determination above 0.99 and identified operating conditions with an energy consumption of 0.6 kWh·m −3 and water recovery of up to 80%. Despite challenges in novel membrane discovery and preparation optimization, this field holds vast development potential. For desalination membranes, AI plays a dual role: significantly improving membrane performance and providing innovative research tools for future membrane design. This helps drive the creation of desalination membranes while speeding up their commercialization and real-world deployment, offering efficient, renewable options for sustainable development.