Author(s): Yaghoobian S; An J; Jeong DW; Hwang JH;

Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into Per- and polyfluoroalkyl substances (PFAS) research; however, the field remains fragmented with substantial variation in modeling objectives. This review provides one of the most comprehensive and detailed syntheses to date of AI/ML methods across the PFAS contaminatio ...

Article GUID: 41483514

Author(s): Yaghoobian S; Ramirez-Ubillus MA; Zhai L; Hwang JH;

Per- and polyfluoroalkyl substances (PFAS) are highly persistent synthetic chemicals that pose severe environmental and health risks, prompting increasingly stringent regulations. The recent crises caused by PFAS contamination underscore the urgent need for rapid, sensitive, and on-site monitoring, along with effective removal and degradation from water s ...

Article GUID: 40656524