Faculty of Physics, Lomonosov Moscow State University, Moscow, Russia.
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia.
Spectrochim Acta A Mol Biomol Spectrosc. 2023 Feb 5;286:122003. doi: 10.1016/j.saa.2022.122003. Epub 2022 Oct 22.
The present study is devoted to the creation of multifunctional optical carbon dots-based nanosensor to simultaneously measure concentrations of metal ions (Cu, Ni, Cr) and NO 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 Cu, Ni, Cr, NO 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 Cu, Ni, Cr 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.
本研究致力于创建基于多功能光学碳点的纳米传感器，以同时测量液体介质中金属离子（Cu、Ni、Cr）和 NO 阴离子的浓度。这种纳米传感器基于其在介质中离子影响下的荧光（FL）变化来工作。然而，缺乏描述 CD FL 机制的分析模型，以及在碳点（CD）与阳离子相互作用过程中各种荧光猝灭机制的叠加，阻碍了使用经典方法来解决这个反多参数光谱问题。为此，使用神经网络分析了包含 Cu、Ni、Cr、NO 离子的 CD 水悬浮液在 0 到 4.95 mM 浓度范围内的复杂荧光信号。以下神经网络架构确保了解决光学光谱反问题：多层感知器、1D 和 2D 卷积神经网络。所开发的传感器能够同时测定重金属离子 Cu、Ni、Cr 的浓度，其均方根误差分别为 0.28 mM、0.79 mM、0.24 mM。根据文献中的数据，我们可以断言，所研究的纳米传感器的准确性满足监测废水和工艺水成分的需求。所开发的纳米传感器具有独特的多模态性：通过简单的合成方案，该传感器能够同时测定三种重金属离子的浓度，而类似的传感器主要是为了测量一种（在极少数情况下为两种）重金属离子的浓度而开发的。
