Synthesis, Characterization, and Evaluation of Co-MOF Based ZIF-67 for CO2 Corrosion Inhibition of X65 Steel: Insights from Electrochemical Studies and a Machine Learning Algorithm

Co-MOF based metal organic framework was synthesized by reacting a metal ion (cobalt nitrate hexahydrate) with an organic ligand (2-methylimidazole) via a wet chemical method. The resulting material was characterized using detailed analytical methods and further was used as a self-assembly corrosion inhibitor in sweet corrosive environment. The empirical data set via electrochemical studies was modeled using adaptive neuro fuzzy inference system (ANFIS). The observed results showed that Co-MOF could significantly impede the corrosion rate of X65 steel and protect it from CO2 corrosion. Increasing the concentration of Co-MOF in the test solution increased the inhibition efficiency up to 97% at 0.1 wt % Co-MOF with a mixed-type inhibition mechanism. In addition, the DFT/MD-simulation approach evidenced the adsorption disposition of Co-MOF in aqueous and gas phase which complement with the empirical findings. Also, the prognostic capability of the proposed algorithm based on the statistical parameters such as root-mean-square error (RMSE), chi square (χ2), model predictive error (MPE) and coefficient of determination (R2) were appraised. From the viewpoint of statistics, the explanatory model aligned credibly with the ANFIS algorithm. The overall findings confirmed a dense hybrid coating of the synthesized Co-MOF on X65 steel as responsible for the inhibition of the sweet corrosion.