Smartphone-integrated multi-color ratiometric fluorescence portable optical device based on deep learning for visual monitoring of Cu2+ and thiram

Lü, Zhiwei; Chen, Maoting; Li, Mengjiao; Liu, Tao; Sun, Mengmeng; Wu, Chun; Su, Gehong; Yin, Jinling; Wu, Mingjun; Zou, Ping; Li, Lin; Wang, Xianxiang; Huang, Qianming; Yin, Huadong; Rao, Hanbing; Zhou, Xinguang; Ye, Jianshan; Wang, Yanying

doi:10.1016/j.cej.2022.135686

Cited by 69 publications

(22 citation statements)

References 74 publications

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“…As shown in Figure C, there existed no overlap between the UV–vis absorbance peak of HVA and Al 3+ and the emission peak, suggesting that the fluorescence quenching mechanism was not attributed to FRET and IFE . Additionally, there was no shift in UV–vis absorbance spectra between the two templates, and the fluorescence sources coexisted as shown in Figure D, indicating that the determination of HVA and Al 3+ did not belong to static quenching . Thus, the quenching mechanism could be attributed to the PET.…”

Section: Resultsmentioning

confidence: 95%

Ratiometric Fluorescence Capillary Sensor-Integrated Molecular Imprinting for Simultaneous Detection of Two Biological Indicators of Parkinson’s Disease

Tang

Zhao

et al. 2022

Anal. Chem.

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This work proposed ratiometric fluorescence capillary sensing systemintegrated molecular imprinting with highly sensitive and selective detection for two biological indicators of Parkinson's disease (homovanillic acid (HVA) and Al 3+ ). In this research, the silicon carbon quantum dot and the near-infrared CdTe quantum dot as luminescence sources were doped to an imprinted layer, which was attached to the inner surface wall of an amino-functionalized capillary. The fluorescence emissions of the ratiometric fluorescence capillary-imprinted sensor at 434 and 707 nm were quenched by HVA, and only the fluorescence emission at 434 nm was quenched by Al 3+ . Ratiometric fluorescence capillary sensing system-integrated molecular imprinting was used to detect simultaneously HVA and Al 3+ with linearity over 1.0 × 10 −9 −2.5 × 10 −7 and 1.0 × 10 −9 −1.1 × 10 −7 M, respectively. The sensor showcased detection limitations of 8.7 × 10 −10 and 9.8 × 10 −10 M, indicating that the ratiometric fluorescence capillary sensing system-integrated molecular imprinting had great potential application for detecting HVA and Al 3+ in serum and urine samples. The ratiometric fluorescence capillary sensing system-integrated molecular imprinting achieved highly sensitive and selective detection of HVA and Al 3+ with a microvolume test dosage of 18 μL, which provided a new way for early diagnosis and disease monitoring of Parkinson's disease.

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Section: Resultsmentioning

confidence: 95%

Ratiometric Fluorescence Capillary Sensor-Integrated Molecular Imprinting for Simultaneous Detection of Two Biological Indicators of Parkinson’s Disease

Tang

Zhao

et al. 2022

Anal. Chem.

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“…For example, the deep learning-assisted smartphone WeChat applet built by our team in the previous work integrated a tricolor fluorescence sensing system, which achieves fast and accurate field detection of pesticides and Cu 2+ . 18 The construction of a ratiometric measurement system is a relatively complicated process, 19 and it is essential to design a suitable monochrome probe. Additionally, the probes must have excellent photoluminescence properties as well as good water stability to exhibit more stable and noticeable color changes in the fluorescence spectrum.…”

Section: Introductionmentioning

confidence: 99%

“…This strategy is more obvious and easier to visually inspect. For example, the deep learning-assisted smartphone WeChat applet built by our team in the previous work integrated a tricolor fluorescence sensing system, which achieves fast and accurate field detection of pesticides and Cu 2+ …”

Section: Introductionmentioning

confidence: 99%

“…Considering the importance of Hg 2+ and S 2– measurement in actual applications, it is usually essential to simplify the detection process to achieve rapid detection of Hg 2+ and S 2– . Our group has realized the rapid detection of pesticides, glucose, heavy metal ions, and food additives by colorimetric or fluorescent strategies based on smartphones. As an important branch of artificial intelligence, machine learning has been used for audio recognition, speech recognition, computer vision, and bioinformatics .…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning System To Monitor Hg²⁺ and Sulfide Using a Polychromatic Fluorescence-Colorimetric Paper Sensor

Lü

Chen

Liu

et al. 2023

ACS Appl. Mater. Interfaces

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An optical monitoring device combining a smartphone with a polychromatic ratiometric fluorescence-colorimetric paper sensor was developed to detect Hg2+ and S2– in water and seafood. This monitoring included the detection of food deterioration and was made possible by processing the sensing data with a machine learning algorithm. The polychromatic fluorescence sensor was composed of blue fluorescent carbon quantum dots (CDs) (BU-CDs) and green and red fluorescent CdZnTe quantum dots (QDs) (named GN-QDs and RD-QDs, respectively). The experimental results and density functional theory (DFT) prove that the incorporation of Zn can improve the stability and quantum yield of CdZnTe QDs. According to the dynamic and static quenching mechanisms, GN-QDs and RD-QDs were quenched by Hg2+ and sulfide, respectively, but BU-CDs were not sensitive to them. The system colors change from green to red to blue as the concentration of the two detectors rises, and the limits of detection (LOD) were 0.002 and 1.488 μM, respectively. Meanwhile, the probe was combined with the hydrogel to construct a visual sensing intelligent test strip, which realized the monitoring of food freshness. In addition, a smartphone device assisted by multiple machine learning methods was used to text Hg2+ and sulfide in real samples. It can be concluded that the fabulous stability, sensitivity, and practicality exhibited by this sensing mechanism give it unlimited potential for assessing the contents of toxic and hazardous substances Hg2+ and sulfide.

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“…Recently, smartphone-based detection methods have been developed, which have a great opportunity to be adopted by normal people due to their convenience [ 6 – 8 ]. For instance, an analyte may cause a color or fluorescence change in a sensor/probe [ 9 – 11 ]. These sensors can be developed by test chips, which may show a visible color change in the presence of a certain amount of the analyte [ 12 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

Promising instrument-free detections of various analytes using smartphones with Spotxel® Reader

et al. 2022

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In consideration of the problems related to food safety, environmental pollution, and the spread of infected diseases nowadays, we urgently need testing methods that can be easily performed by common people. Smartphone-based detections are promising for general applications. However, some of these analytical strategies require a combination of accessories and instruments, such as portable electrochemical workstations, mini multi-mode microplate readers, and complex temperature control devices, etc., which are small but still expensive. Herein, we comprehensively introduce a free app (Spotxel ® Reader) that can provide accurate data analysis for microplate or parallel-format test sensors without an instrument. By simulating the optical signal of the test samples through a smartphone, the sensing results can be obtained for free. We discuss the detection strategies involved in the reported smartphone-based analyses using Spotxel ® Reader. Prospects for the development of this free app for future detection applications are presented. This review aims to popularize free analysis software, so that ordinary people may realize convenient tests. Graphical abstract

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Smartphone-integrated multi-color ratiometric fluorescence portable optical device based on deep learning for visual monitoring of Cu2+ and thiram

Cited by 69 publications

References 74 publications

Ratiometric Fluorescence Capillary Sensor-Integrated Molecular Imprinting for Simultaneous Detection of Two Biological Indicators of Parkinson’s Disease

Ratiometric Fluorescence Capillary Sensor-Integrated Molecular Imprinting for Simultaneous Detection of Two Biological Indicators of Parkinson’s Disease

Machine Learning System To Monitor Hg²⁺ and Sulfide Using a Polychromatic Fluorescence-Colorimetric Paper Sensor

Promising instrument-free detections of various analytes using smartphones with Spotxel® Reader

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Smartphone-integrated multi-color ratiometric fluorescence portable optical device based on deep learning for visual monitoring of Cu2+ and thiram

Cited by 69 publications

References 74 publications

Ratiometric Fluorescence Capillary Sensor-Integrated Molecular Imprinting for Simultaneous Detection of Two Biological Indicators of Parkinson’s Disease

Ratiometric Fluorescence Capillary Sensor-Integrated Molecular Imprinting for Simultaneous Detection of Two Biological Indicators of Parkinson’s Disease

Machine Learning System To Monitor Hg2+ and Sulfide Using a Polychromatic Fluorescence-Colorimetric Paper Sensor

Promising instrument-free detections of various analytes using smartphones with Spotxel® Reader

Contact Info

Product

Resources

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Machine Learning System To Monitor Hg²⁺ and Sulfide Using a Polychromatic Fluorescence-Colorimetric Paper Sensor