Microporous Polymer-Modified Glassy Carbon Electrodes for the Electrochemical Detection of Metronidazole: Experimental and Theoretical Insights.
Héctor Quiroz-ArturoCarlos ReinosoUllrich ScherfAlex Palma-CandoPublished in: Nanomaterials (Basel, Switzerland) (2024)
The persistence and potential toxicity of emergent pollutants pose significant threats to biodiversity and human health, emphasizing the need for sensors capable of detecting these pollutants at extremely low concentrations before treatment. This study focuses on the development of glassy carbon electrodes (GCEs) modified by films of poly-tris(4-(4-(carbazol-9-yl)phenyl)silanol (PTPTCzSiOH), poly-4,4'-Di(carbazol-9-yl)-1,1'-biphenyl (PCBP), and poly-1,3,5-tri(carbazol-9-yl)benzene (PTCB) for the detection of metronidazole (MNZ) in aqueous media. The films were characterized using electrochemical, microscopy, and spectroscopy techniques, including scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Monomers were electropolymerized through cyclic voltammetry and chronoamperometry techniques. Computational methods at the B3LYP/def2-TZVP level were employed to investigate the structural and electrochemical properties of the monomers. The electrochemical detection of MNZ utilized the linear sweep voltammetry technique. Surface characterization through SEM and XPS confirmed the proper electrodeposition of polymer films. Notably, MPN-GCEs exhibited higher detection signals compared to bare GCEs up to 3.6 times in the case of PTPTCzSiOH-GCEs. This theoretical study provides insights into the structural, chemical, and electronic properties of the polymers. The findings suggest that polymer-modified GCEs hold promise as candidates for the development of electrochemical sensors.
Keyphrases
- label free
- gold nanoparticles
- human health
- electron microscopy
- ionic liquid
- high resolution
- molecularly imprinted
- loop mediated isothermal amplification
- risk assessment
- room temperature
- single molecule
- solid state
- heavy metals
- oxidative stress
- pseudomonas aeruginosa
- sensitive detection
- computed tomography
- machine learning
- magnetic resonance imaging
- staphylococcus aureus
- high throughput
- quantum dots