Understanding and Designing a High-Performance Ultrafiltration Membrane Using Machine Learning.

ABSTRACT: Ultrafiltration (UF) as one of the mainstream membrane-based technologies has been widely used in water and wastewater treatment. Increasing demand for clean and safe water requires the rational design of UF membranes with antifouling potential, while maintaining high water permeability and removal efficiency. This work employed a machine learning (ML) method to establish and understand the correlation of five membrane performance indices as well as three major performance-determining membrane properties with membrane fabrication conditions. The loading of additives, specifically nanomaterials (A_wt %), at loading amounts of >1.0 wt % was found to be the most significant feature affecting all of the membrane performance indices. The polymer content (P_wt %), molecular weight

SUBMITTER: Gao H 

PROVIDER: S-EPMC10666290 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature