Scholarlink

The hydroxyl radical (•OH), with a redox potential of 2.8 V, is the most reactive oxygen species involved in various chemical and biological processes. Therefore, the development of simple and reliable methods for its quantitative determination is highly desirable. In this study, an electrochemical sensor based on screen-printed electrodes, DS110 modified with naphthol blue black (NBB) dye, was developed for the detection of generated hydroxyl radicals (•OH). The degradation of the NBB film was induced by •OH radicals generated by the Fenton reaction. The effects of different parameters, such as the H₂O₂ (0.3–2.5 mM) concentration, FeSO₄ (0.03–0.25 mM) concentration, and pH (1–8), on the charge transfer resistance (Rct) and double layer capacitance (Cm) were extracted and analyzed. The experimental results were also modeled via an artificial neural network (ANN) with a mean squared error of 10–5. This model was developed in MATLAB via a feed-forward back-propagation network, a multilayered perceptron. The input variables to the feed-forward neural network were various experimental variables, such as temperature, NNB concentration, FeSO₄ concentration, pH, and H₂O₂ concentration. The ANN successfully modeled the nonlinear relationships between the experimental inputs and the double-layer capacitance (Cm), achieving high predictive accuracy with a coefficient of determination (R2) exceeding 0.99.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development and Optimization of an Electrochemical Sensor for Hydroxyl Radical Detection via DS110 Electrodes and Neural Network Modeling

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Chafia Bouasla,
  • Mohammed Mahdi,
  • Imadeddine Belhani,
  • Saidi Mohamed Racim,
  • Kharoua Amira

摘要

The hydroxyl radical (•OH), with a redox potential of 2.8 V, is the most reactive oxygen species involved in various chemical and biological processes. Therefore, the development of simple and reliable methods for its quantitative determination is highly desirable. In this study, an electrochemical sensor based on screen-printed electrodes, DS110 modified with naphthol blue black (NBB) dye, was developed for the detection of generated hydroxyl radicals (•OH). The degradation of the NBB film was induced by •OH radicals generated by the Fenton reaction. The effects of different parameters, such as the H₂O₂ (0.3–2.5 mM) concentration, FeSO₄ (0.03–0.25 mM) concentration, and pH (1–8), on the charge transfer resistance (Rct) and double layer capacitance (Cm) were extracted and analyzed. The experimental results were also modeled via an artificial neural network (ANN) with a mean squared error of 10–5. This model was developed in MATLAB via a feed-forward back-propagation network, a multilayered perceptron. The input variables to the feed-forward neural network were various experimental variables, such as temperature, NNB concentration, FeSO₄ concentration, pH, and H₂O₂ concentration. The ANN successfully modeled the nonlinear relationships between the experimental inputs and the double-layer capacitance (Cm), achieving high predictive accuracy with a coefficient of determination (R2) exceeding 0.99.