Per-
and polyfluoroalkyl substances (PFAS) constitute a class of
synthetic compounds with exceptional interfacial properties. Their
widespread use in many industrial applications and consumer products,
combined with their remarkable chemical and thermal stability, has
led to their ubiquitous presence in environmental matrices, including
surface water and groundwater. To replace PFAS with fluorine-free
surfactants, it is necessary first to develop a deep molecular-level
understanding of the mechanisms responsible for the exceptional properties
of PFAS. For instance, it has been shown that fluorine-free surfactants
with highly branched or methylated chains can achieve low surface
tensions at air–water interfaces and can provide highly hydrophobic
surface coatings. Although molecular simulations combined with experiments
are promising for uncovering these mechanisms, the reliability of
simulation results depends strongly on the accuracy of the force fields
implemented. At the moment, atomistic force fields are not available
to describe PFAS in a variety of environments. Ab initio methods could
help fill this knowledge gap, but they are computationally demanding.
As an alternative, ab initio calculations could be used to develop
accurate force fields for atomistic simulations. In this work, a new
algorithm is proposed, which, built from accurate ab initio calculations,
yields force fields for perfluorinated sulfonic and perfluoroalkyl
acids. The accuracy of the new force field was benchmarked against
solvation free energy and interfacial tension data. The new force
fields were then used to probe the interfacial behavior of the PFAS
surfactants. The interfacial properties observed in our simulations
were compared with those manifested by two branched fluorine-free
surfactants. The good agreement achieved with experiments and ab initio
calculations suggests that the proposed protocol could be implemented
to study other perfluorinated substances and help in the design of
fluorine-free surfactants for targeted applications.