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A Review on Membrane Biofouling: Prediction, Characterization, and Mitigation
Nour AlSawaftah1,2, Waad Abuwatfa1,2, Naif Darwish1
1Department of Chemical and Biological Engineering, College of Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates.
Membranes
|December 23, 2022
Summary
Water scarcity drives desalination innovation. Membrane technology offers efficient water purification, but biofouling hinders performance. Artificial intelligence aids in predicting and mitigating this challenge.
Area of Science:
- Environmental Science
- Chemical Engineering
- Materials Science
Background:
- Global water scarcity necessitates advanced water treatment solutions like desalination.
- Membrane-based desalination offers energy efficiency and cost-effectiveness but faces challenges.
- Membrane fouling, particularly biofouling, significantly impairs desalination performance and integrity.
Purpose of the Study:
- To provide a comprehensive overview of membrane biofouling in desalination.
- To discuss mechanisms, characterization, and prediction methods for biofouling.
- To highlight the role of artificial intelligence in addressing biofouling challenges.
Main Methods:
- Review of existing literature on membrane biofouling mechanisms.
- Analysis of various biofouling characterization techniques.
- Exploration of artificial intelligence (AI) applications in biofouling prediction.
Main Results:
- Biofouling is the most detrimental type of membrane fouling.
- AI demonstrates high accuracy and adaptive capabilities in predicting membrane fouling.
- Effective characterization and prediction are crucial for mitigation strategies.
Conclusions:
- Membrane technology is vital for addressing water scarcity.
- Understanding and predicting biofouling are critical for optimizing desalination processes.
- AI-powered predictive models offer a promising approach to manage and mitigate membrane biofouling.
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