Detection of Perfluorooctanoic and Perfluorodecanoic Acids on a Graphene-Based Electrochemical Sensor Aided by Computational Simulations
Abstract
Perfluoroalkyl carboxylic acids (PFCAs) exhibit high chemical and thermal stability, rendering them versatile for various applications. However, their notable toxicity poses environmental and human health concerns. Detecting trace amounts of these chemicals is crucial to mitigate risks. Electrochemical sensors surpass traditional methods in sensitivity, selectivity, and cost-effectiveness. In this study, a graphene nanosheet-based sensor was developed for detecting perfluorooctanoic acid (PFOA) and perfluorodecanoic acid (PFDA). Using the Hummer method, graphene nanosheets were synthesized and characterized in terms of morphology, structural ordering, and surface topology. Ab initio molecular dynamics simulations determined the molecular interaction of per- and poly-fluoroalkyl substances (PFASs) with the sensor material. The sensor exhibited high sensitivity (50.75 μA·μM-1·cm-2 for PFOA and 29.58 μA·μM-1·cm-2 for PFDA) and low detection limits (10.4 nM for PFOA and 16.6 nM for PFDA) within the electrode dynamic linearity range of 0.05-500.0 μM (PFOA) and 0.08-500.0 μM (PFDA). Under optimal conditions, the sensor demonstrated excellent selectivity and recovery in testing for PFOA and PFDA in environmental samples, including spiked soil, water, spoiled vegetables, and fruit samples.
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