Perfluoroalkyl substances (PFAS) are a family of over seven million chemicals found in a vast number of industrial and consumer applications. Often referred to as the "forever chemicals," they have gained increasing attention due to their environmental and health implications. The growing awareness and interest in these perfluorinated pollutants demand the exploitation of an integrated approach where the use of computational pipelines can play a major role in the understanding and prediction of their behavior. To this end, we developed an accurate and transferable coarse-grain PFAS model in the framework of the Martini 3 force field. Given the large amount of PFAS already reported, 18 linear perfluorocarboxylic acids and perfluorosulfonic acids of different chain lengths were considered in the parametrization. The model was validated following the standard Martini procedure and complemented with additional studies on self-aggregation and the interaction with graphene, which is a common substrate for sensors and wastewater remediation adsorbents. The results are highly consistent with both all-atom simulations and experimental data, successfully reproducing the key structural and physical properties. We believe that our study opens the way for high-throughput simulations to explore the interaction between PFAS and nanoparticles/(bio)molecules.
Calza et al. (Mon,) studied this question.