Research of synthesis and neural network training on double quantum dot colorimetric fluorescent probe for freshness detection

Abstract

There are many disadvantages such as small detection range and environmental restrictions on application conditions, when the single quantum dot powder or solution is used for fluorescent probe detection. In this paper, the blue fluorescent silicon quantum dots and green fluorescent carbon quantum dots were prepared, and their fluorescence color changes after mixing in different proportions were investigated under different pH conditions. When the two quantum dots were mixed with a concentration of 0.1 mg·mL^–1 and a mass ratio of 1:1, the fluorescence color change could be better displayed at a pH from 1 to 14. Meanwhile, the double quantum dots were prepared into two forms (ink and film), successfully realizing the device application of the fluorescent probe. The films and inkjet-printed labels were used to test the spoilage of food (pork, milk, etc.), and the color change data of the labels were collected during the spoilage test. These data were used for neural network training to predict the spoilage changes of foods.

Key words： silicon quantum dots; carbon quantum dots; fluorescent probe; pH; freshness

Competing interests

The authors declare that they have no competing interests.

Acknowledgements

The authors acknowledge the usage of all characterizations supported by the “14th Five-Year Plan” National Key Research and Development Plan Project (Grant No. 2023YFE0105500), and National Natural Science Foundation of China (Grant No. 52173206). The authors also thank the Core Facility of Wuhan University for FTIR, Fluorescence Spectrophotometer, TGA, and TEM.

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11705-024-2471-8 and is accessible for authorized users.

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