Intelligent Colorimetric Detection of Urinary Zinc
A colorimetric test paper with specific responsiveness to zinc,employing the chromogenic agent Zincon,has been designed and prepared.Upon the addition of a borate buffer solution with a pH of 9.O,the test paper exhibits a red color.Following the complexation of Zincon with zinc in the test sample,the color of the test paper transitions from red to blue.A standard curve is plotted using the color values in the R channel of the test paper,enabling quantitative determination of zinc content in urine.A colorimetric protection mechanism has been established,utilizing polyacrylonitrile(PAN)and polyvinylpyrrolidone(PVP)as carriers,with electrospinning employed to ensure the reproducibility of the colorimetric sensor preparation.Addressing spectral interference issues in colorimetric paper,a machine learning model-Deep Convolutional Neural Networks(DCNN)algorithm has been employed,demonstrating favorable predictive accuracy.This algorithm has been integrated into a smartphone application,contributing to the formation of a comprehensive urine zinc analysis system that integrates"rapid sampling,data processing and transmission,real-time,and visual detection."The method achieves detection limits as low as 0.1 mg/L,making it applicable for non-invasive pre-diagnosis of diseases.The system is characterized by its low cost,rapid detection,ease of operation,high precision,and accuracy.
万方数据
维普
