Quadruple analyte responsive platform: Point-of-care testing and multi-coding logic computation based on metal ions recognition and selective response

Facile synthesis of multicolor emitting sulfur quantum dots and their applications in light blocking field, anti-counterfeiting and sensing

Sulfur quantum dots (SQDs) have aroused widespread interest from researchers in a wide range of fields due to their excellent photoluminescent properties. Ethylenediamine, diaminopropane and butanediamine were used as precursor amine raw materials to interact with sublimated sulfur to synthesize SQDs with blue, cyan and green fluorescence emission, respectively. Multicolour emitting SQDs were first prepared via sulfur-amine interactions. Further characterization and calculations showed that the precursor amine substances could alter growth size and band gap energy of SQDs to allow for a wider absorption and fluorescence transfer to long wavelength emission region, resulting in tunable fluorescence emission. In terms of application, the excellent down-conversion properties of SQDs were utilized to obtain highly transparent and flexible photoblocking films by blending SQDs with polyvinyl alcohol matrixes, achieving a blocking of light in UV region of up to 99.69 %. In addition, we constructed an encoded storage microarray based on standard 8-bit ASCII character binary codes using BSQDs and GSQDs to store and encrypt important information. Finally, GSQDs-based fluorescent sensors were designed to achieve fluorescent trace detection of o-nitrophenols with limits of detection as low as 2.54 μM. The multicolor emitting SQDs prepared in this work have great potential for applications in analytical detection, optical anti-counterfeiting and light blocking.

Sulfur dots and iron co-doped nickel-based metal-organic frameworks with high nanozyme activity for the colorimetric determination of α-glucosidase activity

Alpha-glucosidase (α-Glu) plays a crucial role in regulating the normal physiological function of the body; therefore, α-Glu activity detection is crucial in clinical studies. In this study, a nickel-based metal-organic framework (Ni-MOF) co-doped with sulfur dots (SDs) and iron (Fe) was designed and constructed for the colorimetric detection of α-Glu. The SDs/Fe/Ni-MOF shows a very low Michaelis-Menten constant (0.0466 mM) for H2O2, suggesting a very high affinity for H2O2. Additionally, the free radicals generated by the nanozyme-catalyzed reaction were analyzed, and the feasibility of the nanozyme-catalyzed process was further verified using density functional theory. The bimetallic (Fe and Ni) can improve the catalytic activity of the material, and sulfur can improve the affinity with the substrate to further enhance the catalytic performance. Notably, hydroquinone (HQ) inhibits nanozyme activity, whereas α-Glu hydrolyzes alpha-arbutin (α-Arb) and subsequently produces HQ. Therefore, this study developed a method for detecting α-Glu activity using α-Arb as a substrate. This method has high selectivity, a wide detection range (1.00-100 U L-1), and a low detection limit (0.525 U L-1). Finally, the method was used to α-Glu activity detected in serum samples with good accuracy. This study provides a new method for the detection of α-Glu.

An enzymatic activity regulation-based clusterzyme sensor array for high-throughput identification of heavy metal ions

The accurate identification and sensitive quantification of heavy metal ions are of great significance, considering that pose a serious threat to environment and human health. Most array-based sensing platforms, to date, utilize nanozymes as sensing elements, but few studies have explored the application of the peroxidase-like activity of clusterzymes in identification of multiple analytes. Herein, for the first time, we developed a clusterzyme sensor array utilizing gold nanoclusters (AuNCs) as sensing elements for five heavy metal ions identification including Hg²⁺, Pb²⁺, Cu²⁺, Cd²⁺ and Co²⁺. The heavy metal ions can differentially regulate the peroxidase-like activity of AuNCs, and that can be converted into colorimetric signals with 3,3',5,5'-tetramethylbenzidine (TMB) as the chromogenic substrate. Subsequently, the generated composite responses can be interpreted by combining pattern recognition algorithms. The developed clusterzyme sensor array can identify five heavy metal ions at concentrations as low as 0.5 μM and their multi-component mixtures. Especially, we demonstrated the successful identification of multiple heavy metal ions in tap water and traditional Chinese medicine, with an accuracy of 100% in blind test. This study provided a simple and effective method for identification and quantification of heavy metal ions, rendering a promising technique for environmental monitoring and drug safety assurance.