Application of CD and Eu3+ Dual Emission MOF Colorimetric Fluorescent Probe Based on Neural Network in Fe3+ Detection. (22nd August 2022)

• Record Type: Journal Article
• Authors: Zheng, Yuewei; Wang, Xuan; Guan, Zhihao; Deng, Junjie; Liu, Xinghai; Li, Houbin; Zhao, Pingping
• Is Part Of: Particle and particle systems characterization. Volume 39:Number 10(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-22
• Subjects: carbon dots -- ion detection -- metal‐organic frameworks -- neural networks; Particles -- Periodicals; 620.43
• DOI: 10.1002/ppsc.202200124
• Languages: English
• ISSNs: 0934-0866

Abstract

Abstract: A new highly fluorescent hybrid material (CD@Eu‐MOF) is synthesized by encapsulating carbon dots (CD) prepared from citric acid and ethylenediamine on the basis of a metal‐organic framework (MOF) prepared from Eu 3+ and 1, 2, 4‐benzenetricarboxylic acid. The prepared composite not only maintains the excellent fluorescence properties of CD and Eu 3+, respectively, but also forms a dual‐emission fluorescence system, and the system has good stability in an aqueous solution. It is further used as a novel fluorescent probe for the detection of Fe 3+, which can effectively exclude the interference of other metal ions from the detection, and the intensity ratio of I Eu /I CD of CD@Eu‐MOF material has a good linear relationship with Fe 3+ in the range of 1–200 µm . In this study, computer vision and backpropagation (BP) neural networks are used to train and fit the sample data, and it is verified that the actual fluorescence color of CD has a good linear relationship with Fe 3+ concentration. In addition, the BP neural network also verifies that the fluorescence spectrum data of CD@Eu‐MOF also have a good linear relationship with Fe 3+ concentration. This study provides a new method for the fabrication of ratio and colorimetric Fe 3+ fluorescence sensors. Abstract : In this study, a novel dual‐emission fluorescent material (CD@Eu‐MOF) is proposed for the detection of Fe 3+ . At the same time, computer vision and neural networks are used to study the relationship between fluorescence color and Fe 3+ concentration. A new method is provided for the fabrication of colorimetric Fe 3+ fluorescence sensors.