Smart and Sustainable Regeneration of Fouled Desalination Membranes Using Artificial Intelligence

Abstract

During the desalination process, scaling, fouling, and degradation are associated issues that lead to a drop in the separation performance of membranes. Membrane regeneration emerges as a critical technology in which upcycling and downcycling can offer a promising avenue for promoting sustainable membrane lifecycle management. Multiple research papers and reviews have critically analyzed the regeneration of membranes, which explains the end-of-cycle assessment and cost analysis of membrane recycling. However, challenges associated with the conventional and innovative regeneration processes are not yet analyzed. The potential impact of artificial intelligence (AI) on membrane regeneration is not explained in the literature. This review paper aims to explore the synergistic relationship between AI and membrane regeneration, elucidating the principles, challenges, opportunities, and emerging trends in this rapidly evolving field. By examining the role of AI techniques in enhancing the understanding, monitoring, and control of regeneration membrane processes, as well as their applications in optimizing regeneration strategies and addressing end-of-life considerations, this paper seeks to provide insights into the transformative potential of AI in reshaping the landscape of membrane regeneration.