Retracted Article: Triple signalling mode carbon dots-based biodegradable molecularly imprinted polymer as a multi-tasking visual sensor for rapid and “on-site” monitoring of silver ions†
The present work describes the fabrication of a low-cost, simple, and highly selective analytical method based on the unique combination of fluorescent carbon dots (CDs) and molecularly imprinted polymers (MIPs) for sensitive visual detection of silver ions at trace levels in real samples in both outdoors and at-home. For the first time, fluorescein dye is used as a precursor for the preparation of CDs. The prepared CDs have low toxicity, high stability, good quantum yield, and are free from the common problems (low stability, weak fluorescence intensity, and fast photo-bleaching) of commercially available dyes. The CDs modified MIP (CDs@MIP) has been successfully applied in calligraphy and staining of 3-D crafted papers. In addition, the prepared CDs@MIP has demonstrated the triple-signalling mode trace-level detection of silver ions, in which a simple CDs@MIP solution was sufficient to monitor the presence of silver ions in real and complex matrices with the naked eye, i.e. instrument-free analysis (detection limit = 10.0 μg L−1). The CDs@MIP modified filter-paper strips can be used for the very handy, safe, sensitive, semi-quantitative and rapid detection of silver ions (response time <10 seconds). The silver ions present in real and complex samples (like human blood, urine, wastewater, silver cream and polymetallic ore) are easily analyzed and visually monitored by the strip as well as the solution-phase CDs@MIP sensor. The prepared CDs@MIP shows negligible cytotoxicity towards MCF-7 cells, and has therefore been successfully explored for live cell imaging and intracellular analysis of silver ions. The simple preparation, fast detection (<10 seconds), low cost, easy-handling and layman operation strategy demonstrate that the proposed sensor has potential as a practical and portable sensing interface for wide application in complex matrix analysis.