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A Predictive Model for Corrosion Inhibition of Mild Steel by Thiophene and Its Derivatives Using Artificial Neural Network

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Figure

Table 1. Molecular structures of thiophene and ten of its derivatives.
Figure 1. Structure of artificial neural network
Figure 2. Cathodic and anodic polarization curves recorded for the mild steel electrode in aerated stagnant 0.5 M H2SO4 solutions, at a scan rate of 5 mV s-1 at 25oC1, without and with various thiophene and its derivatives
Table 2. Electrochemical polarization parameters for mild steel in absence and presence of 0.01 M of thiophene and ten of its derivatives in 0.5 M sulfuric acid at 25oC1
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