Dual-Emission Single Sensing Element-Assembled Fluorescent Sensor Arrays for the Rapid Discrimination of Multiple Surfactants in Environments

Abstract

Surfactants are considered as typical emerging pollutants, their extensive use of in disinfectants has hugely threatened the ecosystem and human health, particularly during the pandemic of coronavirus disease-19 (COVID-19), whereas the rapid discrimination of multiple surfactants in environments is still a great challenge. Herein, we designed a fluorescent sensor array based on luminescent metal−organic frameworks (UiO-66-NH 2 @Au NCs) for the specific discrimination of six surfactants (AOS, SDS, SDSO, MES, SDBS, and Tween-20). Wherein, UiO-66-NH 2 @Au NCs were fabricated by integrating UiO-66-NH 2 (2aminoterephthalic acid-anchored-MOFs based on zirconium ions) with gold nanoclusters (Au NCs), which exhibited a dualemission features, showing good luminescence. Interestingly, due to the interactions of surfactants and UiO-66-NH 2 @Au NCs, the surfactants can differentially regulate the fluorescence property of UiO-66-NH 2 @Au NCs, producing diverse fluorescent "fingerprints", which were further identified by pattern recognition methods. The proposed fluorescence sensor array achieved 100% accuracy in identifying various surfactants and multicomponent mixtures, with the detection limit in the range of 0.0032 to 0.0315 mM for six pollutants, which was successfully employed in the discrimination of surfactants in real environmental waters. More importantly, our findings provided a new avenue in rapid detection of surfactants, rendering a promising technique for environmental monitoring against trace multicontaminants.

Monitoring Different Water Types for Engine Oil–Water-Soluble Fraction and Iron(2+) Using a Reaction-Based Optical Sensing Strategy: A Proof-of-Concept Study

“…Chemical sensor arrays with optical signal measurement have been developed to detect model organic pollutants in water, such as pesticides or surfactants, but there are few publications on recognition of individual samples of natural water . The present study is aimed to establish the feasibility of applying the reaction-based optical fingerprinting strategy to the discrimination of clean water samples; another task was to recognize artificially contaminated samples.…”