Georgia Tech researchers, led by Yongsheng Chen, the Bonnie W. and Charles W. Moorman IV Professor in environmental engineering, are at the forefront of a groundbreaking initiative to combat PFAS, or “forever chemicals,” in drinking water. These persistent pollutants, found in everyday items like makeup and nonstick cookware, pose significant health risks, including immune system suppression and increased cancer risk. The team’s innovative approach, funded by over $10 million in grants from the USDA, NSF, and EPA, leverages machine learning (ML) to design a superior membrane for efficient PFAS removal.
Conventional water treatment methods often fall short in eliminating PFAS, and can even create harmful byproducts. Chen’s team is tackling this challenge head-on by separating PFAS from water using advanced membrane materials. The process, which involved a collaborative effort with the University of Wisconsin-Madison and Arizona State University, utilized ML to accelerate the discovery of effective membrane candidates. This interdisciplinary approach not only speeds up the research process but also provides deeper insights into PFAS transport across membranes.
The implications of this research extend beyond drinking water. PFAS contamination in agriculture, particularly in fertilizers derived from wastewater biosolids, poses a significant threat to farmland and livestock. By developing an effective membrane, the team aims to reclaim contaminated resources, supporting both urban and rural areas. The ultimate goal is to achieve a circular economy where materials are continuously reused, and nature is regenerated.
The team will continue to refine their ML model and synthesize membranes to test PFAS removal predictions. The ability to eliminate both long and short chains of PFAS could revolutionize water treatment and environmental remediation.
