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Electrochemical Degradation of Venlafaxine on Platinum Electrodes: Identification of Transformation Products by LC-MS/MS and In Silico Ecotoxicity Assessment

Angelica Rebecca Zizzamia, Veronica Pasquariello, Filomena Lelario, Carmen Tesoro, Rosanna Ciriello

Molecules, 2025

4 citations

Abstract

Antidepressants are emerging contaminants that have raised global concern due to their abuse. Venlafaxine (VFX), a serotonin and norepinephrine reuptake inhibitor, can cause adverse and potentially toxic effects on aquatic organisms. Electrochemical advanced oxidation processes (EAOPs) are gaining attention as promising degradation techniques for a variety of drugs. EAOP methods proposed for VFX degradation mainly utilize boron-doped diamond (BDD) electrodes, characterized by low background current and high oxygen overpotential. However, challenges arise, including delamination from the substrate, difficulties in scaling up, and limited service life. In this study, platinum was employed as an anode for the galvanostatic degradation of VFX, due to its stability and well-established surface cleaning procedure, which ensured high reproducibility. A 0.1 M Na2SO4 solution at pH 9 was used as the supporting electrolyte, and a current density of 25 mA/cm2 was applied. After 7 h, a degradation efficiency of 94% was achieved for a 25 ppm VFX solution. The hydroxyl and sulfate radicals generated in the electrochemical system were the active species responsible for VFX degradation, which followed a first-order kinetic model with a rate constant of 0.0084 min−1. The main degradation intermediates were identified through LC-MS, including two isomers with a nominal m/z of 276 and three isomers with a nominal m/z of 294. The toxicity of the VFX degradation products was assessed by an in…

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Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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