Per- and polyfluoroalkyl substances (PFAS) are a group of persistent, toxic chemicals known for their resistance to degradation. Found in a range of products from non-stick cookware to firefighting foams, these “forever chemicals” accumulate in the environment and in human tissue, posing long-term health risks such as thyroid disorders, cancers, and immune system impairment.
Detecting PFAS is difficult because they are present at extremely low concentrations. Traditional detection methods, such as liquid chromatography coupled with tandem mass spectrometry, are highly accurate but take time and require specialized equipment. Analyses can take weeks, an obstacle to enforcing increasingly strict safety standards, including the EPA’s new limit of 4 parts per trillion for PFOS and PFOA.
For years, researchers have sought faster, cheaper, and field-deployable alternatives. With over 15 years of experience developing portable, chip-based water sensors, the team behind the study has adapted its platform, previously used for lead detection, to address the PFAS challenge.
The scientists, from Argonne National Laboratory and the University of Chicago’s Pritzker School of Molecular Engineering (PME), have developed a remote gate field-effect transistor sensor featuring a β-cyclodextrin (β-CD)-modified reduced graphene oxide membrane. This combination has enabled the detection of PFOS in tap water at concentrations around 250 parts per quadrillion, significantly below the EPA’s threshold.
The sensor operates as a handheld, portable device that uses tailored molecular probes to identify PFAS: PFOS, and perfluorooctanoic acid (PFOA), in minutes.
Refined through computer simulations and machine learning, the device was optimized for both the sensitivity and selectivity of the molecular probes. These probes are engineered to recognize the distinctive molecular features of PFAS, allowing accurate detection even in complex water samples.
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How it Works
The sensor measures changes in electrical conductivity when PFOS molecules bind to its surface. Achieving specificity was a significant challenge during R&D, as thousands of PFAS compounds share similar structures. To overcome this, the team used machine learning algorithms to rapidly screen potential probe molecules and identify those most selective for individual PFAS variants.
In experiments, one probe demonstrated strong specificity for PFOS, showing little interference from other chemicals commonly found in tap water. When PFOS binds to the probe, it triggers measurable conductivity shifts proportional to its concentration. To verify accuracy, the researchers cross-checked sensor readings with EPA-approved mass spectrometry methods, confirming excellent agreement.
Significance and Future Directions
The sensor’s results matched laboratory-grade analytical techniques, but contrary to lab analysis, provided speed, reversibility, and robustness. It maintained accuracy across multiple detection and rinsing cycles and responded in under two minutes, which is ideal for continuous, real-time monitoring.
Further analysis of molecular dynamics simulations and quartz crystal microbalance studies revealed that charge interactions and adsorption behaviors play key roles in probe design and sensor performance. The system also demonstrated high selectivity, remaining unaffected by natural organic matter, common ions, or other pollutants.
The researchers plan to extend their technology to detect a broader range of PFAS compounds. Their devices could support widespread, on-site water quality testing, helping consumers and regulators identify contamination events more rapidly and accurately.
Journal Reference
Wang, Y. et al. (2025). Reversible parts-per-trillion-level detection of perfluorooctane sulfonic acid in tap water using field-effect transistor sensors. Nature Water, 1-11. DOI: 10.1038/s44221-025-00505-9, https://www.nature.com/articles/s44221-025-00505-9
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