Fluorescence Anion Chemosensor Array Based on Pyrenylboronic Acid

Organic acid-induced triple fluorescent emission carbon quantum dots identification of distilled liquor

An acid-sensitive carbon dot fluorescence sensing array was investigated for the differentiated recognition of distilled spirits. Due to the electrostatic interactions between CDs and organic acids, organic acids affect the protonation and fluorescence properties of CDs, which in turn modify the CDs triple fluorescence emission. The regular linear variation of the fluorescence sensor was found under acidic conditions (3.0 < pH < 6.2). A comprehensive study of acids with selectivity, different concentrations (0.1 mM, 1 mM, 10 mM, 40 mM), different types (8 species) and mixed acids (formic acid and acetic acid), and good quantification capability for acetic acid (0.01-1 mM). Demonstrating good recognition ability of the sensor array for complex analyte. On this basis, the fluorescence sensor array was applied to the classification and recognition of liquors. LDA has realized the identification of 16 kinds of Baijiu and 21 kinds of distilled liquors with an accuracy of 100%.

Carbon Quantum Dots Based Chemosensor Array for Monitoring Multiple Metal Ions

The simultaneous identification of multiple metal ions in water has attracted enormous research interest in the past few decades. We herein describe a novel method for multiple metal ion detection using a carbon quantum dots (CQDs)-based chemosensor array and the CQDs are functionalized with different amino acids (glutamine, histidine, arginine, lysine and proline), which act as sensing elements in the sensor array. Eleven metal ions are successfully identified by the designed chemosensor array, with 100% classification accuracy. Importantly, the proposed method allowed the quantitative prediction of the concentration of individual metal ions in the mixture with the aid of a support vector machine (SVM). The sensor array also enables the qualitative detection of unknown metal ions under the interference of tap water and local river water. Thus, the strategy provides a novel high-throughput approach for the identification of various analytes in complex systems.

Toward a Selective Analysis of Heavy Metal Salts in Aqueous Media with a Fluorescent Probe Array

Detection of heavy meals in aqueous media challenges worldwide research in developing particularly fast and affordable methods. Fluorescent sensors look to be an appropriate instrument for such a task, as recently they have been found to have made large progress in the detection of chemical analytes, primarily in the environment, along with biological fluids, which still suffer from not enough selectivity. In this work, we propose a new fluorescent method to selectively recognize heavy metals in an aqueous solution via employing an array of several fluorescent probes: acridine yellow, eosin, and methylene blue, which were taken as examples, being sensitive to a microsurrounding of the probe molecules. The exemplary sensor array generated six channels of spectral information through the use of various combinations of excitation and detection wavelengths. Following the known multisensor approach, we applied a linear discriminant analysis to selectively distinguish the vector signals from the sensor array from salts of heavy metals-Cu, Pb, Zn, Cd, and Cz-at the concentration ranges of 2.41 × 10-6-1.07 × 10-5 M, 2.8 × 10-5-5.87 × 10-4 M, 1.46 × 10-6-6.46 × 10-6 M, 1.17 × 10-8-5.2 × 10-8 M, and 2.11 × 10-6-9.33 × 10-6 M, respectively. The suggested approach was found to be promising due to it employing only one cuvette containing the test solution, simplifying a sample preparation when compared to preparing a variety of solutions in tests with single fluorescence probes.

Toward Food Freshness Monitoring: Coordination Binding-Based Colorimetric Sensor Array for Sulfur-Containing Amino Acids

Herein, a self-assembled colorimetric chemosensor array composed of off-the-shelf catechol dyes and a metal ion (i.e., Zn2+) has been used for the sulfur-containing amino acids (SCAAs; i.e., glutathione, glutathione disulfide, L-cysteine, DL-homocysteine, and L-cystine). The coordination binding-based chemosensor array (CBSA) fabricated by a competitive assay among SCAAs, Zn2+ ions, and catechol dyes [i.e., pyrocatechol violet (PV), bromopyrogallol red (BPR), pyrogallol red (PR), and alizarin red S (ARS)] yielded fingerprint-like colorimetric changes. We succeeded in the qualification of SCAAs based on pattern recognition [i.e., a linear discrimination analysis (LDA)] with 100% correct classification accuracy. The semiquantification of reduced/oxidized forms of SCAAs was also performed based on LDA. Furthermore, we carried out a spike test of glutathione in food samples using the proposed chemosensor array with regression analysis. It is worth mentioning that we achieved a 91-110% recovery rate in real sample tests, which confirmed the accuracy of the constructed model. Thus, this study represents a step forward in assessing food freshness based on supramolecular analytical methods.