Machine Learning-Driven Advances in Polymer Membrane Science: Emerging Trends and Future Directions

Document Type : Review Paper

Authors

1 Nitte (Deemed to be University), NMAM Institute of Technology (NMAMIT), Nitte,Department of Electronics and Communication Engineering, Karkala-574110,India

2 Nitte (Deemed to be University),NMAM Institute of Technology (NMAMIT), Nitte, Department of Electronics and Communication Engineering,Karkala-574110,India

3 Nitte (Deemed to be University),NMAM Institute of Technology (NMAMIT), Nitte, Department of Biotechnology, Karkala-574110,India

4 Membrane and Separation Technology Laboratory, Department of Chemistry, National Institute of Technology, Karnataka, Surathkal, Mangalore- 575025,India

5 Membrane and Separation Technology Laboratory, Department of Chemistry, National Institute of Technology Karnataka, Surathkal, India

10.22104/aet.2025.7210.1990

Abstract

Membrane science is gaining importance in the emerging field due to its fewer energy consumption and low maintenance. Many surveys and studies were concentrating on specific membranes for specific appli-cations. Trial-and-error approaches in membrane design result in inefficiencies, including time and material wastage. There is a need for developing a generalized model with minimal parameters and resulting mem-brane satisfying separation applications. Enhancement of membrane performance is crucial and hence many researchers considered the fabrication and design aspects of membrane parameters as research crite-ria for different applications. High surface area, ease of maintenance, and low cost make them attractive to different applications including the bio-medical sector, food and beverages, water filtration, gaseous envi-ronment, etc. However, membrane design and configuration demand several experiments specific to the applications. Hence it is still considered to be a challenging process thus opening new avenues towards automating the process. This review comprises a summary of state-of-the-art membrane technology and its application in the separation phenomenon providing a machine learning perspective in membrane science and engineering.

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Articles in Press, Accepted Manuscript
Available Online from 05 December 2025
  • Receive Date: 15 November 2024
  • Revise Date: 20 November 2025
  • Accept Date: 05 December 2025