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首页> 外文期刊>RSC Advances >Parameters affecting carbon nanofiber electrodes for measurement of cathodic current in electrochemical sensors: an investigation using artificial neural network
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Parameters affecting carbon nanofiber electrodes for measurement of cathodic current in electrochemical sensors: an investigation using artificial neural network

机译：影响电化学传感器中阴极电流测量的碳纳米纤维电极的参数：使用人工神经网络的研究

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摘要

The aim of this work was to investigate the effective parameters for predicting the cathodic current in a polyacrylonitrile-based carbon nanofiber (CNF) electrode using an artificial neural network (ANN) method. The various factors including CNF diameter, CNF layer thickness, electrodeposition time of Pt on the CNF electrode, and pH of a phosphate buffer solution (PBS) containing K3Fe (CN)(6) were designed to investigate the cathodic current of the CNF electrode. The different samples of the electrodes were fabricated as training and testing data-sets for ANN modeling. The best network had one hidden layer with 10 nodes in the layer. The mean squared error (MSE) and linear regression (R) between the observed and predicted cathodic current were 0.0763 and 0.9563, respectively, confirming the performance of the ANN. The obtained results using cyclic voltammetry (CV) exhibited that the cathodic current improves with decreasing CNF diameter, CNF layer thickness, electrodeposition time of Pt on the CNF electrode and solution pH.
机译：该工作的目的是使用人工神经网络（ANN）方法来研究用于预测聚丙烯腈基碳纳米纤维（CNF）电极中的阴极电流的有效参数。设计了CNF电极上的CNF直径，CNF层厚度，Pt的电沉积时间的各种因子，以及含有K3Fe（CN）（6）的磷酸盐缓冲溶液（PBS）的pH值以研究CNF电极的阴极电流。电极的不同样品被制造为ANN建模的训练和测试数据集。最好的网络在图层中有一个带有10个节点的隐藏层。观察和预测的阴极电流之间的平均平方误差（MSE）和线性回归（R）分别为0.0763和0.9563，确认了ANN的性能。使用循环伏安法（CV）的得到的结果表明，阴极电流随着CNF直径的降低而改善，CNF层厚度，PT的电沉积时间和溶液pH。

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  • 来源
    《RSC Advances》 |2015年第99期|共10页
  • 作者

    Adabi Mahdi; Saber Reza; Naghibzadeh Majid; Faridbod Farnoush; Faridi-Majidi Reza;

  • 作者单位

    Univ Tehran Med Sci Sch Adv Technol Med Dept Med Nanotechnol Tehran Iran;

    Univ Tehran Med Sci Sch Adv Technol Med Dept Med Nanotechnol Tehran Iran;

    Shahid Sadoughi Univ Med Sci Res &

    Clin Ctr Infertil Dept Nanotechnol Yazd Iran;

    Univ Tehran Ctr Excellence Electrochem Fac Chem Tehran Iran;

    Univ Tehran Med Sci Sch Adv Technol Med Dept Med Nanotechnol Tehran Iran;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 化学;
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