Corrosion inhibition by Myristica fragrans extract in neem biodiesel: Evaluation by machine learning and traditional methods

Abstract

Ethyl acetate extract of Myristica fragrans mace flowers was investigated as an effective inhibitor for copper in neem biodiesel. Employing the ASTM D130 method to assess copper corrosion in biodiesel, a remarkable inhibition efficiency of 98.04% was achieved. Inhibitor adsorption on the surface of copper metal was substantiated by FTIR spectral evaluation. Surface morphology studies by SEM confirmed the protective nature of the inhibitor for copper metal corrosion prevention. Further, several support vector machine (SVM) learning algorithms were employed with three different classes of corrosion to study the corrosion inhibition of which, the medium Gaussian procedure gave a maximum accuracy of 92.4%. The work reveals the applicability of the SVM algorithm for accurate corrosion estimation and classification not only in biodiesel medium but also in various environments.