journal article·2024-01

ZIF-8/CNFs/PANI composite as an electrochemical platform in trace-level nitrite sensing

Suma B. Patri, Supritha M. Karekuladh, Pandurangappa Malingappa

Carbon Letters· Volume 34· Issue 1
Publisher page

Abstract

Zeolitic imidazolate frameworks (ZIFs) along with carbon nanofibers and polyaniline composite have been explored as an electrochemical sensing platform in nitrite measurement at trace level. Owing to their topology, high surface area and porous structure, these metal–organic frameworks (MOFs) find widespread utility in different application domains. Nitrites are widely used as preservatives in dairy, meat products, and packaged food stuffs. They form N-nitrosamines, which are potential carcinogens and cause detrimental health effects. These ZIF-based MOFs along with carbon nanofibers and polyaniline have emerged as an efficient electrochemical sensing material. The composite has been characterized by X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and BET surface area studies. The electrochemical performance of the composite has been evaluated by forming as a thin film of composite on the surface of glassy carbon electrode and studying its impedance as well as electrochemical sensing behavior. The sensor exhibited good analytical response in nitrite measurement with a limit of detection of 8.1 µM. The developed sensing platform has been successfully applied to quantify the nitrite levels from water samples. The results obtained are in good agreement with the results of standard protocol. Graphical abstract Schematic representation of fabrication of ZIF-8/CNF/PANI composite-modified electrode and its application in electrochemical sensing of nitrite.
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Research context

OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Electrochemical sensors and biosensors · Metal-Organic Frameworks: Synthesis and Applications

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

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