Unfolding the electrocatalytic efficacy of highly conducting NiFe2O4-rGO nanocomposites on the road to rapid and sensitive detection of hazardous p-Nitrophenol

NiFe2O4 nanoparticles (NPs) and NiFe2O4-reduced graphene oxide (NiFe2O4-rGO(X), X = 5, 10, 15 and 20 wt% of GO) nanocomposites (NCs) based electrocatalysts have been synthesized by hydrothermal method and employed for the first time in the direct and sensitive determination of perilous p-Nitrophenol (PNP) using Square Wave Anodic Stripping Voltammetry (SWASV). The designed composites have been characterized using Powder-XRD, RAMAN spectroscopy, FTIR, VSM, FESEM, DRS and BET to investigate their physicochemical properties. The NC NiFe2O4-rGO(10)-modified Glassy Carbon Electrode (NiFe2O4-rGO(10)/GCE) displayed a considerably high catalytic current response towards the irreversible reduction of PNP and was therefore chosen for further studies. The proposed method has intriguing attributes including (i) one-pot synthesized non-toxic and low-cost sensing material, (ii) calibration curve (recorded between -0.5 to -1.5 V vs. Ag/AgCl at scan rate of 50 mV/s) with an exceptionally broader linear relationship for PNP ranging from 0.5 mu M to 21.0 mu M and 21.0 mu M to 4000 mu M separately, with a remarkably low detection limit of 45 nM under optimized conditions, and (iii) practical applicability of the proposed sensor for the determination of PNP in samples acquired from different water sources with outstanding recoveries (>95%). The constructed sensor holds excellent reproducibility with rapid regeneration; long-last durability and good selectivity which indicated that proposed sensor NiFe2O4-rGO(10)/GCE can be a promising tool for electrochemical analysis of PNP.

Automated summary

NiFe2O4-rGO(X) nanocomposites were synthesized and employed for sensitive detection of perilous p-Nitrophenol (PNP) using Square Wave Anodic Stripping Voltammetry (SWASV). Characterization techniques confirmed the excellent electrocatalytic properties of NiFe2O4-rGO(10) composites for PNP analysis.