Zubair Hashmi, Ibrahim Maina Idriss, Femiana Gapsari, Norazanita Samsuddin, Muhammad Roil Bilad
Nanomaterial-enhanced membranes offer a promising solution for water treatment, improving permeability, selectivity, and fouling resistance. However, their integration into existing systems requires further exploration, particularly in real-world conditions. This systematic review focuses on key nanomaterials—graphene oxide, carbon nanotubes, metal-organic frameworks, and MXenes—evaluating their effectiveness in removing emerging contaminants and enhancing membrane longevity. The review synthesizes findings from recent literature on nanomaterial properties, performance metrics, experimental techniques, and case studies, providing a comprehensive evaluation. It highlights the superior contaminant rejection, antifouling properties, and structural enhancements of nanomaterial-based membranes compared to conventional systems. Despite these advantages, challenges such as high production costs, scalability issues, environmental concerns, and regulatory barriers hinder widespread adoption. Further research is needed to develop cost-effective synthesis methods, sustainable production, and environmentally safe disposal practices. Additionally, artificial intelligence and machine learning offer promising opportunities for optimizing membrane design and accelerating the development of advanced filtration technologies. This study contributes to the knowledge base by identifying key research gaps and proposing future directions, emphasizing the integration of artificial intelligence, machine learning, and sustainable practices in nanomaterial-enhanced membranes, with the goal of advancing their large-scale implementation for sustainable water purification. © 2025 The Author(s)
Faculty of Integrated Technologies, Universiti Brunei Darussalam, Jalan Tungku Link, BE, Gadong, 1410, Brunei Darussalam; Department of Mechanical Engineering, Faculty of Engineering, Brawijaya University, Haryono 167, MT, Malang, 65145, Indonesia
