A Multi-Modal Spectroelectrochemical Sensor Platform for the Real-Time Detection of Per- and Polyfluoroalkyl Substances (PFAS) using Advanced Data Fusion

Objective

"Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants associated with serious health risks, including chronic diseases and cancer. Widely used in various industries, they are known as ""forever chemicals"" due to their stability. While traditional detection methods like LC-MS/MS are accurate, they are costly and time-consuming, making them impractical for on-site, real-time monitoring. With regulatory actions, such as the European REACH proposal seeking to restrict PFAS use, there is a critical need for faster, portable detection technologies. This project addresses this challenge through the development of an integrated, real-time monitoring system based on multi-modal spectroelectrochemistry. My innovative approach combines electrochemical and optical (fluorescence/absorbance) detection by using a specialized redox-active probe. This strategy enhances detection sensitivity and robustness by requiring a correlated, two-dimensional signature for a valid detection, significantly reducing the risk of false positives that limit current single-signal sensors. Core objectives include the systematic characterization of these multi-modal probe-PFAS interactions, the development of advanced multivariate models to deconvolve the complex datasets, and the design of a portable platform that integrates these methods. This project will be the first to systematically develop and validate a multi-modal spectroelectrochemical sensor for priority PFAS compounds. By delivering an accessible, high-confidence, real-time detection tool, we aim to improve environmental monitoring, helping regulators and industries better manage PFAS contamination and protect public health."