journal article·2021-09Open access

Photoelectrocatalysis of paracetamol on Pd–ZnO/ N-doped carbon nanofibers electrode

Amr A. Nada, Benjamin O. Orimolade, Heba H. El-Maghrabi, Babatunde A. Koiki, Matthieu Rivallin, Maged F. Bekheet, Roman Viter, Daina Damberga, Geoffroy Lesage, Igor Iatsunskyi, Emerson Coy, Marc Cretin, Omotayo A. Arotiba, Mikhael Bechelany

Abstract

Abstract The presence of pharmaceuticals in water bodies has become a major concern in recent years. An efficient and innovative way of eliminating these pollutants is through photoelectrocatalytic (PEC) degradation owing to its environmental sustainability and its ability to remove recalcitrant pollutants. In this study, palladium loaded zinc oxide/carbon nanofibers (CZnO–Pd) were employed as a novel photoanode for PEC degradation of paracetamol. The CZnO–Pd composite was prepared through electrospinning and atomic layer deposition (ALD). The obtained materials were characterized. Photoelectrochemical studies were carried out with linear sweep voltammetry and chronoamperometry. The removal efficiency was recorded using high-performance liquid chromatography coupled to a mass spectrometer detector (HPLC-MS), while the mineralization was assessed through total organic carbon (TOC) removal. The composite electrode of CZnO–Pd nanofiber showed higher photoelectrochemical activity than ZnO carbon nanofiber, which was evident in the higher photocurrent response recorded. Upon application of the material in photoelectrocatalysis, the total removal of paracetamol was achieved within 3 h with an applied current density of 10 mAcm−2. The percentage of TOC removal was 71.20 ± 0.31% after 4 h, which indicated significant mineralization. The results obtained in the present work reveal that Pd–ZnO/C has great potential for photoelectrocatalytic removal of organic micropollutants.
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Research context

OpenAlex topics: Advanced Photocatalysis Techniques · Pharmaceutical and Antibiotic Environmental Impacts · Advanced oxidation water treatment

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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