Quantitative estimation of cod values from an array of metal nanoparticle modified electrodes and artificial neural networks “2279

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SUMMARY

    Chemical oxygen demand (COD) is a widely used parameter in the evaluation of the total organic compounds present in water, especially in wastewater. In light of this consideration, a more powerful and flexible technique for nonlinear regression attracted us, namely, artificial neural_networks (ANNs). The following metallic NPs were used as modifiers during the fabrication of the electrodes: copper (Cu NPs, 40~60 nm) and copper (II) oxide (CuO NPs, and amp;lt;50 nm) which were purchased from Sigma-Aldrich (St. Louis, MO, USA), and nickel copper alloy (Ni Cu NPs, and amp;lt . . .

     

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