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Recent advances in fluorescence-based chemosensing of organoarsenic feed additives using luminescence MOFs, COFs, HOFs, and QDs
R. Mondal, A. Shanmughan, A. Murugeswari,
Published in Royal Society of Chemistry
2023
PMID: 37674461
Volume: 59
   
Issue: 77
Pages: 11456 - 11468
Abstract
Organoarsenics are low-toxicity compounds that are used widely as feed additives to promote livestock growth, enhance meat pigmentation, and fight against intestinal parasites. The organoarsenic compounds are commonly found in poultry waste and the degradation of organoarsenic produces the toxic carcinogen inorganic arsenic such as As(v) and As(iii), which results in severe arsenic pollution of soil and groundwater. As a consequence, there exists a high necessity to develop suitable sensing methods for the trace detection and quantification of organoarsenic feed additives in wastewater. Among various detection methods, in particular, fluorescence-based sensing has become a popular and efficient method used extensively for sensing water contaminants and environmental contaminants. In the recent past, a wide variety of fluorescence chemosensors have been designed and employed for the efficient sensing and quantification of the concentration of organoarsenic feed additives in different environmental samples. This review article systematically highlights various fluorescence chemosensors reported to date for fluorescence-based sensing of organoarsenic feed additives. The fluorescence sensors discussed in this review are classified and grouped according to their structures and functions, and in each section, we provide a detailed report on the structure, photophysics, and fluorescence sensing properties of different chemosensors. Lastly, the future perspectives on the design and development of practically useful sensor systems for selective and discriminative sensing of organoarsenic compounds have been stated. © 2023 The Royal Society of Chemistry.
About the journal
JournalChemical Communications
PublisherRoyal Society of Chemistry
ISSN13597345
Open AccessNo