New Indole Derivative Heterogeneous System for the Synergistic Reduction and Oxidation of Various Per-/Polyfluoroalkyl Substances: Insights into the Degradation/Defluorination Mechanism

Electrostatic Field in Contact-Electro-Catalysis Driven C-F Bond Cleavage of Perfluoroalkyl Substances

Perfluoroalkyl substances (PFASs) are persistent and toxic to human health. It is demanding for high-efficient and green technologies to remove PFASs from water. In this study, a novel PFAS treatment technology was developed, utilizing polytetrafluoroethylene (PTFE) particles (1-5 μm) as the catalyst and a low frequency ultrasound (US, 40 kHz, 0.3 W/cm2) for activation. Remarkably, this system can induce near-complete defluorination for different structured PFASs. The underlying mechanism relies on contact electrification between PTFE and water, which induces cumulative electrons on PTFE surface, and creates a high surface voltage (tens of volts). Such high surface voltage can generate abundant reactive oxygen species (ROS, i.e., O2⋅-, HO⋅, etc.) and a strong interfacial electrostatic field (IEF of 109~1010 V/m). Consequently, the strong IEF significantly activates PFAS molecules and reduces the energy barrier of O2⋅- nucleophilic reaction. Simultaneously, the co-existence of surface electrons (PTFE*(e-)) and HO⋅ enables synergetic reduction and oxidation of PFAS and its intermediates, leading to enhanced and thorough defluorination. The US/PTFE method shows compelling advantages of low energy consumption, zero chemical input, and few harmful intermediates. It offers a new and promising solution for effectively treating the PFAS-contaminated drinking water.

Electrochemical Reduction of Perfluorooctanoic Acid (PFOA): An Experimental and Theoretical Approach

Perfluorooctanoic acid (PFOA) is an artificial chemical of global concern due to its high environmental persistence and potential human health risk. Electrochemical methods are promising technologies for water treatment because they are efficient, cheap, and scalable. The electrochemical reduction of PFOA is one of the current methodologies. This process leads to defluorination of the carbon chain to hydrogenated products. Here, we describe a mechanistic study of the electrochemical reduction of PFOA in gold electrodes. By using linear sweep voltammetry (LSV), an E0' of -1.80 V vs Ag/AgCl was estimated. Using a scan rate diagnosis, we determined an electron-transfer coefficient (αexp) of 0.37, corresponding to a concerted mechanism. The strong adsorption of PFOA into the gold surface is confirmed by the Langmuir-like isotherm in the absence (KA = 1.89 × 1012 cm3 mol-1) and presence of a negative potential (KA = 3.94 × 107 cm3 mol-1, at -1.40 V vs Ag/AgCl). Based on Marcus-Hush's theory, calculations show a solvent reorganization energy (λ0) of 0.9 eV, suggesting a large electrostatic repulsion between the perfluorinated chain and water. The estimated free energy of the transition state of the electron transfer (ΔG‡ = 2.42 eV) suggests that it is thermodynamically the reaction-limiting step. 19F - 1H NMR, UV-vis, and mass spectrometry studies confirm the displacement of fluorine atoms by hydrogen. Density functional theory (DFT) calculations also support the concerted mechanism for the reductive defluorination of PFOA, in agreement with the experimental values.

Novel Defluorination Pathways of Perfluoroether Compounds (GenX): α-Fe2O3 Nanoparticle Layer Retains Higher Concentrations of Effective Hydrated Electrons

The development of efficient defluorination technology is an important issue because the kind of emerging pollutant of hexafluoropropylene oxide dimer acid (GenX) as an alternative to perfluorooctanoic acid (PFOA) has the higher environmental risks. In the UV/bisulfite system, we first developed a hydrophobic confined α-Fe2O3 nanoparticle layer rich in oxygen vacancies, which accelerated the enrichment of HSO3- and GenX on the surface and pores through electrostatic attraction and hydrophobic interaction, retaining more hydrated electrons (eaq-) and rapidly destroying GenX under UV excitation. Especially, under anaerobic and aerobic conditions, the degradation percentage of GenX obtain nearly 100%, defluorination of GenX to 88 and 57% respectively. It was amazed to find that the three parallel H/F exchange pathways triggered by the rapid reactions of eaq- and GenX, which were unique to anaerobic conditions, improved the efficiency of fluoride removal and weaken the interference of dissolved oxygen and H+. Therefore, this study provided an available material and mechanism for sustainable fluoride removal from wastewater in aerobic and anaerobic conditions.

Integrating molecular descriptors for enhanced prediction: Shedding light on the potential of pH to model hydrated electron reaction rates for organic compounds

Hydrated electron reaction rate constant (ke-aq) is an important parameter to determine reductive degradation efficiency and to mitigate the ecological risk of organic compounds (OCs). However, OC species morphology and the concentration of hydrated electrons (e-aq) in water vary with pH, complicating OC fate assessment. This study introduced the environmental variable of pH, to develop models for ke-aq for 701 data points using 3 descriptor types: (i) molecular descriptors (MD), (ii) quantum chemical descriptors (QCD), and (iii) the combination of both (MD + QCD). Models were screened using 2 descriptor screening methods (MLR and RF) and 14 machine learning (ML) algorithms. The introduction of QCDs that characterized the electronic structure of OCs greatly improved the performance of models while ensuring the need for fewer descriptors. The optimal model MLR-XGBoost(MD + QCD), which included pH, achieved the most satisfactory prediction: R2tra = 0.988, Q2boot = 0.861, R2test = 0.875 and Q2test = 0.873. The mechanistic interpretation using the SHAP method further revealed that QCDs, polarizability, volume, and pH had a great influence on the reductive degradation of OCs by e-aq. Overall, the electrochemical parameters (QCDs, pH) related to the solvent and solute are of significance and should be considered in any future ML modeling that assesses the fate of OCs in aquatic environment.