Decoding Fluorescence Excitation-Emission Matrices of Carbon Dots Aqueous Solutions with Convolutional Neural Networks to Create Multimodal Nanosensor of Metal Ions
O. E. Sarmanova, G. N. Chugreeva, K. A. Laptinskiy, S. A. Burikov, S. A. Dolenko, T. A. Dolenko
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引用次数: 0
Abstract
In this study, to create a carbon dots-based multimodal nanosensor of metal ions, a new approach to solving the inverse problem of fluorescence spectroscopy is presented. The problem is to simultaneously determine the concentration of heavy metal ions Cr\({}^{3+}\), Ni\({}^{2+}\), Cu\({}^{2+}\), and nitrate anions NO\({}^{-}_{3}\) in water by carbon dots (CDs) fluorescence spectra. A method of spectral data augmentation is proposed. It is based on the generation of excitation-emission matrices of CDs fluorescence from the noise vector using variational autoencoders and further determination of ion concentration corresponding to the generated matrices with convolutional neural networks. Implementing the proposed approach allowed reducing the mean absolute error in determining the concentration of ions by 60\(\%\) for Cr\({}^{3+}\), by 41\(\%\) for Ni\({}^{2+}\), by 62\(\%\) for Cu\({}^{2+}\), and by 48\(\%\) for NO\({}^{-}_{3}\).
期刊介绍:
Moscow University Physics Bulletin publishes original papers (reviews, articles, and brief communications) in the following fields of experimental and theoretical physics: theoretical and mathematical physics; physics of nuclei and elementary particles; radiophysics, electronics, acoustics; optics and spectroscopy; laser physics; condensed matter physics; chemical physics, physical kinetics, and plasma physics; biophysics and medical physics; astronomy, astrophysics, and cosmology; physics of the Earth’s, atmosphere, and hydrosphere.