Journal
ACS APPLIED NANO MATERIALS
Volume 6, Issue 14, Pages 12946-12956Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsanm.3c01681
Keywords
water pollutants; imprinted polymer; interferometry; selective; p-cresol; opticalbio-sensor
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Selective and susceptible biochemical detection of toxic pollutants in water has long been a challenging task for the scientific community. In this study, a compact, stable, reproducible, and label-free optical sensor using photonic crystal fiber-based modal interferometry and molecular imprinting polymer nanoparticles (MIP-NPs) is developed for the selective detection of p-cresol pollutant in water. The sensor exhibits a remarkable detection ability with an extremely low limit of detection and a broad dynamic detection range.
Selective detection of toxic pollutants present in waterhas beena severe challenge to the scientific community for a long time. Thenoble integration of optical fiber-based interferometry with a bio-recognizingelement molecular imprinting polymer (MIP) exhibits a promising techniquefor selective and susceptible biochemical detection. Here, we reporta compact, stable, reproducible, and label-free optical sensor usinga combined approach of photonic crystal fiber (PCF)-based modal interferometryand MIP nanoparticles (MIP-NPs) for selective detection of water pollutant p-cresol with an extremely low limit of detection (LOD).The MIP-NPs having a greater surface-to-volume aspect ratio allowsmore target analytes to bind. The sensor immobilized with MIP-NPsshows unprecedented sensitivity of 1.865 x 10(8) nm/Mwith specific and repeatable detection performance for a broad dynamicdetection range of 10(-8)-10(-3) M. The sensor offers a remarkable detection ability of as low as1.55 nM concentrations of p-cresol in the aqueousmedium, for water quality monitoring. Fast response, high resolution,compact size, label-free broad detection range, and selective reusableperformance of the proposed sensor exhibit potential for board practicalutilizations, including medical sectors, online and remote biosensing,and water resource monitoring.
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