Issue 8, 2019

Fluorescent organic nanoparticles (FONs) as convenient probes for metal ion detection in aqueous medium

Abstract

Recently, water contamination caused by metal ions has become one of the most serious problems as it has caused several deaths and socioeconomic problems around the world. Hence, the fast and accurate detection of metal ions in aqueous media has become the most important area of research; from time to time, new probes have been designed for this purpose. Among the previously reported sensors, probes based on fluorescent organic nanoparticles (FONs) have been gaining tremendous attention due to their ease of preparation/fabrication, synthetic diversity according to targeted metal ions, quick response, high selectivity toward different analytes at lower concentrations, tenable optical properties, and less toxicity. This review comprises two main sections, wherein we have tried to summarize the key progresses made in this field. The first section summarizes the literature dealing with FON-based chemosensors, which are used for the detection of transition metal ions of silver, copper, chromium, cadmium, mercury, iron, and zinc. The second section focuses on FON-based chemosensors that have been used for the detection of main group metal ions, namely, cesium, aluminum, strontium, lithium, and tin. Further, this review provides an adequate amount of information about the mechanism of metal ion sensing with FONs. It is expected that this review can provide sufficient information about this area of research and will be useful in fruitful progress in this field in the future.

Graphical abstract: Fluorescent organic nanoparticles (FONs) as convenient probes for metal ion detection in aqueous medium

Article information

Article type
Tutorial Review
Submitted
18 Sep 2018
Accepted
21 Feb 2019
First published
25 Feb 2019

Analyst, 2019,144, 2480-2497

Fluorescent organic nanoparticles (FONs) as convenient probes for metal ion detection in aqueous medium

M. Ahmed, M. Faisal, A. Ihsan and M. M. Naseer, Analyst, 2019, 144, 2480 DOI: 10.1039/C8AN01801D

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