Carbon dots as luminescent nanosensors in determining the composition of multicomponent liquid media
K.A. Laptinskiy1,2, G.N. Chugreeva1, A.M. Vervald1, I.V. Plastinin1,2, T.A. Dolenko1
1Lomonosov Moscow State University, Faculty of Physics, Moscow, Russia
2Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics, Moscow, Russia
Keywords: carbon dot, nanosensor, photoluminescence, machine learning method, neural network, perceptron, recurrent neural network
Abstract
The paper presents the results of using carbon dots as luminescent nanosensors of heavy metal ions in aqueous media. The application of machine learning methods to the photoluminescence spectra of nanoparticles in multicomponent aqueous salt solutions made it possible to simultaneously determine the concentrations of desired substances. The comparative analysis of the quality of solving the inverse problem by different neural networks was carried out. Comparison of the results of using neural networks and X-ray fluorescence analysis for determining the ionic composition of industrial process media showed that the accuracy of the developed nanosensor fully meets the requirements for monitoring and controlling the composition of waste and process water.
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