Modification of biochar by iron containing adsorption centers as a method to enhance the remediation of perfluorooctanoic (PFOA) and (PFOS) acids from water and soil: a density functional theory study

Abstract

Perfluoroalkyl and polyfluoroalkyl substances (PFAS), with over 15,000 types listed in the US EPA’s CompTox database, are found in everyday items like textiles, packaging, firefighting foams, and medical devices. Their widespread use has led to concerning health effects—including cancers, elevated cholesterol, and fertility issues—with detectable levels present in 98% of Americans.

While perfluorooctanoic (PFOA) and perfluorooctanesulphonic (PFOS) are among the most studied, their environmental behavior and ecological interactions remain poorly understood. Advances in computer-based methods, including chemoinformatics and quantum modeling, now aid in predicting properties and simulating PFAS dynamics.

Biochar (BC), produced via biomass pyrolysis under limited oxygen, is known for its porosity and adsorption capabilities. Magnetic biochar (MBC), enhanced with iron-based compounds, adds the benefit of magnetic separation, making it ideal for water decontamination. This paper explores the use of MBC to remove PFOA and PFOS from the environment, leveraging computational tools to investigate molecular interactions and adsorption properties.

A doubled crystallographic unit of hematite (Fe₂₄O₃₆) was constructed and fully optimized using density functional theory (DFT) with the M06-2X functional. Geometry optimization used the 6-31G(d,p) basis set, while single-point energies were calculated with 6–311 + + G(d,p). Antiferromagnetic conditions were ensured by setting the total spin to zero (Sz = 0), and triplet instability analysis was performed to evaluate ferromagnetic potential.

To simulate bulk water effects on adsorption, the CPCM solvation model (ε = 78.3) was applied. Harmonic frequency analysis confirmed structural minima, and Gibbs free energies were calculated using Gaussian 16. PFOA and PFOS, with highly negative pKa values (~ –0.1 and <).

Quadratic SCF convergence (scf = qc) addressed numerical challenges, and interaction energies were corrected for basis set superposition error using the counterpoise method. Calculated IR spectra and molecular visualizations were generated with Chemcraft, without applying scaling factors.