Insights into PFAS environmental fate through computational chemistry: A review
Document Type
Article
Publication Date
5-20-2024
Abstract
Per- and polyfluoroalkyl substances (PFAS) are widely used chemicals that exhibit exceptional chemical and thermal stability. However, their resistance to degradation has led to their widespread environmental contamination. PFAS also negatively affect the environment and other organisms, highlighting the need for effective remediation methods to mitigate their presence and prevent further contamination. Computational chemistry methods, such as Density Functional Theory (DFT) and Molecular Dynamics (MD) offer valuable tools for studying PFAS and simulating their interactions with other molecules. This review explores how computational chemistry methods contribute to understanding and tackling PFAS in the environment. PFAS have been extensively studied using DFT and MD, each method offering unique advantages and computational limitations. MD simulates large macromolecules systems however it lacks the ability model chemical reactions, while DFT provides molecular insights however at a high computational cost. The integration of DFT with MD shows promise in predicting PFAS behavior in different environments. This work summarizes reported studies on PFAS compounds, focusing on adsorption, destruction, and bioaccumulation, highlighting contributions of computational methods while discussing the need for continued research. The findings emphasize the importance of computational chemistry in addressing PFAS contamination, guiding risk assessments, and informing future research and innovations in this field.
Identifier
85188652217 (Scopus)
Publication Title
Science of the Total Environment
External Full Text Location
https://doi.org/10.1016/j.scitotenv.2024.171738
e-ISSN
18791026
ISSN
00489697
PubMed ID
38494023
Volume
926
Recommended Citation
de Souza, Bruno Bezerra and Meegoda, Jay, "Insights into PFAS environmental fate through computational chemistry: A review" (2024). Faculty Publications. 416.
https://digitalcommons.njit.edu/fac_pubs/416