Detection of multiple per- and polyfluoroalkyl substances (PFAS) using a biological brain-based gas sensor
May 9, 2026 - Summer Mclane-Svoboda, Shruti Joshi, Autumn McLane-Svoboda, Camron Stout, Maksim Bazhenov and Debajit Saha
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Per- and polyfluoroalkyl substances (PFAS) are man-made, bio accumulative “forever chemicals” that are increasingly found in environmental and biological systems. By leveraging biological chemical sensing systems (i.e., insect olfaction) we can detect broad ranges of PFAS. Insects’ advanced combinatorial coding mechanism at the level of olfactory sensory neurons enables highly sensitive and specific odor detection. Here, we harness the locust olfactory system to differentiate several PFAS. In-vivo extracellular neural recordings displayed unique, reproducible odor-evoked responses for multiple PFAS at environmental concentrations. Population-level response dynamics (i.e., ON and OFF odor-evoked activity), enabled robust neural fingerprinting of compounds. Using high-dimensional neural features and classification analysis, we differentiated seven PFAS simultaneously with 87% accuracy, while concentration range classification reached 84%, including 100% accuracy for environmental-level PFOS. Machine learning algorithms trained on high-concentration (0.01% v/v, ppb) responses and tested on low-concentration (0.0001% v/v, ppt) samples, maintained 69.8% accuracy, demonstrating generalizability across detection regimes. This work presents the first biological olfaction-based PFAS sensing platform, highlighting neural computation as a powerful analytical tool for environmental monitoring. Our findings represent a significant step toward the development of a compact, brain-based PFAS detection sensor capable of discriminating multiple compounds and concentrations simultaneously.
