The National Science Foundation awarded a $465,181 Project Grant to the University of Illinois under the Engineering federal grant program (CFDA 47.041) for the period of September 1, 2022 through August 31, 2025.
The grant funds the development of a low-cost microelectrode sensor array platform coupled with machine learning algorithms to detect per- and polyfluoroalkyl substances (PFAS) in water. PFAS are a class of chemicals used in numerous consumer and industrial products that can contaminate drinking water sources when released into the environment. Current PFAS detection methods rely on expensive chromatography equipment requiring specialized training.
The University of Illinois project aims to create a mobile, affordable alternative for in-situ PFAS monitoring. Researchers will characterize PFAS adsorption mechanisms, conduct computational modeling to guide sensor material selection, and fabricate a machine learning-enabled microelectrode sensor array capable of detecting individual PFAS compounds in water samples with detection limits in the low ng/L range across varying water matrices. The grant also supports research experiences for undergraduate and high school students.
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