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Simultaneous colorimetric determination of dopamine and ascorbic acid based on the surface plasmon resonance band of colloidal silver nanoparticles using artificial neural networks

机译:胶体银纳米粒子表面等离子体共振带同时比色法测定多巴胺和抗坏血酸

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A new method for simultaneous determination of dopamine (DA) and ascorbic acid (ASC) is proposed. The method is based on the reaction of dopamine and ascorbic acid with the oxidizing agent (silver nitrate) in the presence of PVP (as a stabilizer) and the formation of silver nanoparticles in a slightly basic medium. Spectrophotometry is used to monitor the changes of the surface plasmon resonance (SPR) band at a maximum wavelength of silver nanoparticles (440 nm) vs. time. Three-layered feed-forward artificial neural networks (ANN) trained by back propagation learning algorithm is used to model the relationship between absorbance and concentration to quantify analyte in mixtures under optimum conditions. Sigmoidal and linear transfer functions were used in the hidden and output layers, respectively. Linear calibration graphs were obtained in the concentration range of (3.2 × 10?6 – 2.0 × 10?5 mol L?1) for DA and (2.0 × 10?6 – 4.8 × 10?5mol L?1) for ASC. The detection limits were 8.0 × 10?7 and 6.2 × 10?7 mol L?1 for DA and ASC, respectively, which are comparable by different spectrophotometric and colorimetric methods. The method was applied successfully to the determination of dopamine (DA) and ascorbic acid in human serum samples...
机译:提出了一种同时测定多巴胺(DA)和抗坏血酸(ASC)的新方法。该方法基于多巴胺和抗坏血酸与氧化剂(硝酸银)在PVP(作为稳定剂)存在下的反应,并在弱碱性介质中形成银纳米颗粒。分光光度法用于监测银纳米颗粒最大波长(440 nm)随时间变化的表面等离子体共振(SPR)带的变化。通过反向传播学习算法训练的三层前馈人工神经网络(ANN)用于对吸光度和浓度之间的关系进行建模,以在最佳条件下对混合物中的分析物进行定量。分别在隐藏层和输出层中使用了S型和线性传递函数。对于DA,在(3.2×10-6-2.0×10-5 mol L?1)的浓度范围内,对于ASC,在(2.0×10-6-4.8×10-5mol L?1)的浓度范围内获得线性校正图。 DA和ASC的检出限分别为8.0×10?7和6.2×10?7 mol L?1,可通过不同的分光光度法和比色法进行比较。该方法已成功应用于人血清中多巴胺(DA)和抗坏血酸的测定...

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