| Abstract Scope |
The study explored the effectiveness of two types of modified graphene oxide, namely diaminohexane modified graphene oxide and diaminooctane modified graphene oxide, in inhibiting the corrosion of carbon steel in a 15% HCl solution. This investigation employed both weight loss and electrochemical measurement methods at varying temperatures. Analytical techniques including FTIR, Raman, TGA, and TEM confirmed the successful synthesis of GO and its grafting with diaminoalkanes. Thermal analysis indicated that both DAH-GO and DAO-GO are more stable compared to GO. Density Functional Theory calculations were employed to assess the stability of functionalized GOs relative to GO and to understand the interactions between the inhibitor molecules and the steel surface. A dual-modelling scheme to predict the %IE, employing four stand-alone machine learning models (Multivariate Regression (MVR), Gaussian Process Regression (GPR), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Neural Network (NN)), and five ensemble paradigms (MVR-SA, GPR-SA, ANFIS-SA, NN-SA, and Decision Tree-SA (DT-SA)). |