Perfluoroalkyl substances (PFAS) feature an ultra-high resistance to degradation due to the strength of the C—F bonds resulting in persistent environmental contamination. Recent experimental work have shown that both silylium-carborane and activated persulfate catalysts have ability to degrade PFAS compounds. Despite this advancement, key mechanistic details are missing. In the current study, we seek to understand how these catalysts work and be able to develop design strategies for future catalytic systems; consequently, we have embarked on an atomistic study of the relevant elementary steps using state-of-the-art ab initio quantum chemistry methods. The silylium-carborane catalysts is comprised of two parts: a silylium cation, and a caged fluorinated carborane anion. The cation acts as a strong Lewis acid, with the carborane anion acting as a weak Lewis base and anchor. We explore the computational degradation of PFAS molecules by first locating possible binding configurations. It is anticipated that the PFAS will coordinate through carbon centers and fluorine groups on the anion and cation, respectively. Subsequent to binding configurations, defluorination reactions will be identified using the nudged elastic band method (NEB). Previous work on oxidation of PFAS using activated persulfate has computationally identified a principal mechanism for degrading perfluorooctanoic acid (PFOA), however no experimental degradation has been observed for perfluorooctanesulfonic acid (PFOS). We will expand on this work by computationally investigating additional key mechanistic details by evaluating how chain length (C4 vs. C6 vs. C8) and polar head group (CO2 vs. SO3) effect the resulting mechanism. Results from this atomistic computational study on persulfate oxidation will provide insight to how variation in the fluorinated substrates effects the degradation mechanism and overall degradation efficiency.

Developing an atomistic understanding catalyst for PFAS degradation from Ab Initio quantum chemistry

ACS Spring Meeting 2021

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