Issue 3, 2017

Sulfate radical oxidation of aromatic contaminants: a detailed assessment of density functional theory and high-level quantum chemical methods

Abstract

Advanced oxidation processes that utilize highly oxidative radicals are widely used in water reuse treatment. In recent years, the application of sulfate radical (SO4˙) as a promising oxidant for water treatment has gained increasing attention. To understand the efficiency of SO4˙ in the degradation of organic contaminants in wastewater effluent, it is important to be able to predict the reaction kinetics of various SO4˙-driven oxidation reactions. In this study, we utilize density functional theory (DFT) and high-level wavefunction-based methods (including computationally-intensive coupled cluster methods), to explore the activation energies of SO4˙-driven oxidation reactions on a series of benzene-derived contaminants. These high-level calculations encompass a wide set of reactions including 110 forward/reverse reactions and 5 different computational methods in total. Based on the high-level coupled-cluster quantum calculations, we find that the popular M06-2X DFT functional is significantly more accurate for OH additions than for SO4˙ reactions. Most importantly, we highlight some of the limitations and deficiencies of other computational methods, and we recommend the use of high-level quantum calculations to spot-check environmental chemistry reactions that may lie outside the training set of the M06-2X functional, particularly for water oxidation reactions that involve SO4˙ and other inorganic species.

Graphical abstract: Sulfate radical oxidation of aromatic contaminants: a detailed assessment of density functional theory and high-level quantum chemical methods

Article information

Article type
Paper
Submitted
06 Қаң. 2017
Accepted
13 Ақп. 2017
First published
14 Ақп. 2017

Environ. Sci.: Processes Impacts, 2017,19, 395-404

Sulfate radical oxidation of aromatic contaminants: a detailed assessment of density functional theory and high-level quantum chemical methods

S. Pari, I. A. Wang, H. Liu and B. M. Wong, Environ. Sci.: Processes Impacts, 2017, 19, 395 DOI: 10.1039/C7EM00009J

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