Machine learning-driven design of membranes for saline and produced water treatment across scales
Membrane-based desalination technologies are critical for addressing global water scarcity; however, their performance optimization remains a complex challenge.
Authors
- Faheem Hassan Akhtar (ORCID: https://orcid.org/0000-0001-6367-5011)
- Kim Choon Ng (ORCID: https://orcid.org/0000-0003-3930-4127)
- Ahmed A. Abdala (ORCID: https://orcid.org/0000-0002-7398-9118)
- Uzair Ahmad (ORCID: https://orcid.org/0009-0003-1354-9828)
Institutions
- Lahore University of Management Sciences (PK)
- Hamad bin Khalifa University (QA)
- King Abdullah University of Science and Technology (SA)
Publication Details
- Journal
- Environmental Science Water Research & Technology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ew00417a
- Citations
- 3
- Primary Topic
- Membrane Separation Technologies
- Type
- article
- Field-Weighted Citation Impact
- 2.45
Funders
- Lahore University of Management Sciences