Determination of metal ion mixtures using pH gradient flow-injection analysis with fluorescence detection

Implementing neural network approach to create carbon-based optical nanosensor of heavy metal ions in liquid media

The present study is devoted to the creation of multifunctional optical carbon dots-based nanosensor to simultaneously measure concentrations of metal ions (Cu²⁺, Ni²⁺, Cr³⁺) and NO₃^- anion in liquid media. Such nanosensor operates on the basis of its fluorescence (FL) change under the influence of ions in the medium. However, the absence of analytical model, describing CD FL mechanism, the superposition of various luminescence quenching mechanisms during the interaction of carbon dots (CD) with cations, hampers the usage of classical approaches to solve this inverse multiparametric spectroscopic problem. To solve it neural networks were used that analyzed complex fluorescence signal from CD aqueous suspensions comprising Cu²⁺, Ni²⁺, Cr³⁺, NO₃^- ions in the concentration range from 0 to 4.95 mM. The following neural network architectures ensured optical spectroscopy inverse problem solution: multilayer perceptrons, 1D and 2D convolutional neural networks. The developed sensor enables simultaneous determination of the concentrations of heavy metal ions Cu²⁺, Ni²⁺, Cr³⁺ with a root mean squared error of 0.28 mM, 0.79 mM, 0.24 mM respectively. Based on the data given in the literature we can assert that the accuracy of the studied nanosensor satisfies the needs of monitoring the composition of waste and technological water. The developed nanosensor has a unique multimodality: with the simplicity of the synthesis protocol the sensor enables simultaneous determination of three heavy metal ions concentrations, while analogues are being developed mainly to measure the concentration of one (in rare cases two) heavy metal ions.

Development of a novel flow injection liquid-liquid microextraction method for the on-line separation and preconcentration for determination of zinc(II) using 5-(8-hydroxy-2-quinolinylmethyl)-2,8-dithia-5-aza-2,6-pyridinophane as a sensitive and selective fluorescent chemosensor

A novel flow injection analysis (FIA) system based on liquid-liquid microextraction and fluorimetric determination was developed for the determination of traces of the Zn(2+) ion using 5-(8-hydroxy-2-quinolinylmethyl)-2,8-dithia-5-aza-2,6-pyridinophane (L) as a sensitive and selective fluorimetric sensor, with λ(ex)=373 nm and λ(em)=530 nm, and hexanol as the extracting organic solvent. In the designed FIA system, the phase separation takes place via gravitation forces in the absence of any segmenter. The influence of pH and ionic strength of the solution, amount of ligand, nature of counter ion, volume of organic solvent, extraction time and coil length was investigated. Under optimized experimental conditions, the calibration curve found to be liner over a concentration range of 0.025-4.53 μg mL(-1) (R(2)=0.9951) with a limit of detection of 2.3 ng mL(-1). The enrichment factor was 45 and relative standard deviation for 7 replicate determinations was 2.43%. The method is very fast and uses low levels of organic solvents. The proposed method was applied successfully to the determination of zinc(II) in human hair, human serum and two inorganic sludge samples.

High-performance liquid chromatographic separation and indirect fluorescence detection of thiols

A fluorescent post-column reaction detection scheme has been devised for selective determination of thiols. The post-column reagent is 40 microM Cd2+ and 100 microM 8-hydroxyquinoline-5-sulfonic acid (HQS) in non-complexing buffer at pH 10. HQS complexes Cd2+ to form a fluorescent product. Thiols in the HPLC effluent compete for complexation of the Cd2+, resulting in a decrease in the fluorescence response. Detection limits of 0.2 microM (0.04 ppm) are achieved for cysteine, homocysteine and glutathione in a 5 min separation. Recoveries from spiked synthetic urine samples are 87-120%.