ReviewGlobal challenges (Hoboken, NJ)2025
Smart and Sustainable Regeneration of Fouled Desalination Membranes Using Artificial Intelligence.
Review in Global challenges (Hoboken, NJ), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Smart and Sustainable Regeneration of Fouled Desalination Membranes Using Artificial Intelligence.Global challenges (Hoboken, NJ) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.